speech on computer life

Speech on Computer

Computers are magical boxes that help us solve problems and create new things. They are like super-brains that can do calculations and remember things faster than humans.

You use computers every day, from playing games to doing homework. They make our lives easier and more fun.

1-minute Speech on Computer

Ladies and Gentlemen,

Today, I am going to share with you some thoughts on a device that has revolutionized our world – The Computer. The computer, a marvel of technology, is an indispensable tool in our daily life. It has invaded almost every aspect of our life, providing us with new capabilities and enhancing many of our activities.

In the field of education, computers are helping students learn better and faster. They are able to access a world of information at their fingertips, making learning interactive and fun. Computers also enable teachers to demonstrate complex concepts more easily, ensuring a better understanding for students.

In businesses, computers have automated many tasks, thereby increasing productivity and efficiency. They have also opened up a world of opportunities through online businesses. Indeed, many of today’s successful enterprises are based solely on computer operations.

Moreover, in the field of communication, computers have shrunk the world. Today, we can connect with anyone, anywhere in the world, in real time. This has not only brought people closer but also facilitated the exchange of ideas across borders.

However, like any other tool, the computer has its own pitfalls. It is essential that we use it responsibly and not become overly dependent on it. We must also be aware of the various security risks that come with using computers and take proper precautions.

In conclusion, the computer is a wonderful device that has transformed our lives in countless ways. But we must remember to use it wisely and responsibly. Let us harness the power of this amazing tool to further our knowledge and skills, while also being conscious of its potential risks.

Also check:

• Essay on Computer
• Advantages and Disadvantages of Computer

2-minute Speech on Computer

Good afternoon, today I am here to speak on a topic that is integral to our modern life – the ‘Computer’. It is indeed a broad subject, encompassing many aspects, but I will try to simplify it and present it in an easy-to-understand language.

A computer, in its crudest form, is a device that can process data at high speed and accuracy. It can accomplish tasks that would take humans a considerable amount of time and energy, in just a few seconds. The power of the machine lies in its ability to process vast amounts of data and turn it into useful information. But the computer is not just a machine, it is an invention that has revolutionised the way we live and work.

The earliest computers were large, complex machines that occupied entire rooms. They were used mainly for scientific and military applications. However, with the advent of the microprocessor in the 1970s, computers became smaller, cheaper, and more accessible to the general public. Today, computers are everywhere – in our homes, offices, schools, and even in our pockets. We use computers for a wide range of tasks, from writing emails and browsing the internet to designing buildings and diagnosing diseases.

One of the most significant impacts of computers is on communication. Before computers, communicating with someone far away was slow and often unreliable. With computers and the internet, we can now send messages and share information with people all over the world in an instant. This has not only made our personal lives easier but also transformed the way businesses operate.

Computers are also a cornerstone of education. They have changed the way we learn and teach, making education more interactive and engaging than before. With computers, students can access a wealth of information and learning resources from all over the world. They can also learn at their own pace and in their own time, making education more accessible for everyone.

In the field of healthcare, computers have brought about revolutionary changes. They are used for various purposes, from maintaining patient records and managing hospital administration to conducting complex surgeries and researching new drugs. Computers have made healthcare more efficient, accurate, and reliable.

However, like any tool, computers can be used for both good and bad. While they have brought about immense benefits, they have also opened up new avenues for crime, privacy invasion, and addiction. Thus, it is crucial for us to use computers responsibly and educate ourselves about their risks and dangers.

In conclusion, computers have become an integral part of our lives. They have revolutionized the way we work, communicate, learn, and entertain ourselves. They have made our lives easier and more convenient but have also posed new challenges. As we move forward, it is important for us to harness the power of computers for the greater good and to be aware of their potential pitfalls.

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Speech on Computer - 10 Lines, Short and Long Speech

Speech on computer.

A computer is an electronic machine that accepts data and processes it to produce new data as output. Computers first appeared around the period of World War II. However, at the time, only the government had access to computers, and the general population was not permitted to use them. A primary computer includes a mouse, display, keyboard, and CPU. Other attachable parts, such as laser pens, scanners, and printers, can be used.

10 Lines Speech on Computer

1) A computer is an electrical device that executes commands issued by the user.

2) A "programme" is a set of instructions delivered to a computer by the user.

3) The first mechanical computer was constructed by "Charles Babbage" called an "Analytical Engine"; hence, he is recognised as the "Father of the Computer".

4) A computer operates as part of a system that includes an Input Device, an Output Device, a Central Processing Unit (CPU), and a Storage Device.

5) "Input" refers to the raw data and information provided to the computer.

6) Processing is the operation and manipulation of data following the user's instructions; it is entirely an internal computer procedure.

7) "Output" refers to the analytics specified by the computer after processing the user's commands.

8) The word computer is drawn from the Latin word "Computer", which means "to calculate".

9) "Peripherals" are input devices like mice and keyboards and output devices such as printers and monitors.

10) Computers are classified into three sorts based on their usage: analogue, digital, and hybrid.

Short Speech on Computer

Computers have become an integral component of our daily lives. With it, offices, schools, hospitals, governmental organisations, and non-governmental organisations are complete. Our labour, whether schoolwork, office work, or mother's housework, depends on computers.

Uses of Computers

It has a variety of applications. A computer is used in the medical field to diagnose disorders. Because of this computer, they have discovered cures for various diseases. Computers have brought about significant developments in the realm of study. Computers have aided in numerous types of study, including scientific, social, and space research. They have helped keep the environment, society, and play under control.

Computers have also aided in the most vital aspect of a country's economy, namely the military. It aids the country's security authorities in detecting potential threats in the future. The military sector also employs to maintain tabs on our adversary.

Even computers, which have grown so crucial to us, have disadvantages, such as hackers who can steal and publish data on the internet. This information is available to anyone. We must remember that excess of anything is harmful. We should strive to minimise its use because it can be detrimental to our eyes, back, and brain and cause other difficulties.

Long Speech on Computers

Computers have become a vital part of our society and have greatly impacted the way we live and work.

Computers have come a long way since the first mainframe computers were created in the 1940s. These early computers were large and expensive machines that were primarily used by government agencies and large corporations. However, as technology advanced, computers became smaller, more affordable, and more accessible to the general public.

Advantages of Computers

First and foremost, computers have made communication much easier and more efficient. With the internet, we are able to connect with people from all over the world in an instant. We can send emails, instant messages, and make video calls, all from the comfort of our own homes. This has made it possible for people to work remotely and collaborate with others on projects, regardless of their location.

Computers make tasks faster and more efficient. From research projects to writing essays, computers have made it easier for us to complete our work in a shorter amount of time.

Education | Computers also play a major role in the field of education. Online classes, tutorials, and educational videos have made it possible for students to learn at their own pace and on their own schedule.

Entertainment | In the field of entertainment, computers have also had a significant impact. With the rise of streaming services and online gaming, we now have access to a vast library of movies, TV shows, and games.

Business | In the business world, computers have also revolutionised the way companies operate. From data analysis to inventory management, computers have made it possible for businesses to streamline their operations and make better decisions.

Disadvantages of Computers

Computers have greatly impacted our lives in many ways, and their importance cannot be overstated. However, as with any technology, there are also potential downsides to consider. One of the main concerns is the impact of computers on our physical and mental health. Sitting in front of a computer for long periods of time can lead to eye strain, back pain, and other health issues. Additionally, the constant use of computers can lead to feelings of isolation and depression.

It is important to remember that while computers can greatly benefit us, it is also important to use them in moderation and take breaks to engage in physical activities and social interaction.

My Experience

I remember the time when I first got my computer, it was a big deal for me. I was in high school and having a computer at home was a luxury. I was able to do my homework, research, and even connect with my friends. It was a game-changer for me and I believe it can be the same for you all.

In conclusion, computers have greatly impacted our lives in many ways, and their importance cannot be overstated. They have made communication, education, entertainment and business more efficient and accessible. However, it is important to use them in moderation and to be mindful of the potential downsides.

Explore Career Options (By Industry)

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Data Administrator

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Bio Medical Engineer

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Ethical Hacker

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Data Analyst

The invention of the database has given fresh breath to the people involved in the data analytics career path. Analysis refers to splitting up a whole into its individual components for individual analysis. Data analysis is a method through which raw data are processed and transformed into information that would be beneficial for user strategic thinking.

Data are collected and examined to respond to questions, evaluate hypotheses or contradict theories. It is a tool for analyzing, transforming, modeling, and arranging data with useful knowledge, to assist in decision-making and methods, encompassing various strategies, and is used in different fields of business, research, and social science.

Geothermal Engineer

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Database Architect

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Remote Sensing Technician

Individuals who opt for a career as a remote sensing technician possess unique personalities. Remote sensing analysts seem to be rational human beings, they are strong, independent, persistent, sincere, realistic and resourceful. Some of them are analytical as well, which means they are intelligent, introspective and inquisitive. 

Remote sensing scientists use remote sensing technology to support scientists in fields such as community planning, flight planning or the management of natural resources. Analysing data collected from aircraft, satellites or ground-based platforms using statistical analysis software, image analysis software or Geographic Information Systems (GIS) is a significant part of their work. Do you want to learn how to become remote sensing technician? There's no need to be concerned; we've devised a simple remote sensing technician career path for you. Scroll through the pages and read.

Budget Analyst

Budget analysis, in a nutshell, entails thoroughly analyzing the details of a financial budget. The budget analysis aims to better understand and manage revenue. Budget analysts assist in the achievement of financial targets, the preservation of profitability, and the pursuit of long-term growth for a business. Budget analysts generally have a bachelor's degree in accounting, finance, economics, or a closely related field. Knowledge of Financial Management is of prime importance in this career.

Underwriter

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Finance Executive

Product manager.

A Product Manager is a professional responsible for product planning and marketing. He or she manages the product throughout the Product Life Cycle, gathering and prioritising the product. A product manager job description includes defining the product vision and working closely with team members of other departments to deliver winning products.  

Operations Manager

Individuals in the operations manager jobs are responsible for ensuring the efficiency of each department to acquire its optimal goal. They plan the use of resources and distribution of materials. The operations manager's job description includes managing budgets, negotiating contracts, and performing administrative tasks.

Stock Analyst

Individuals who opt for a career as a stock analyst examine the company's investments makes decisions and keep track of financial securities. The nature of such investments will differ from one business to the next. Individuals in the stock analyst career use data mining to forecast a company's profits and revenues, advise clients on whether to buy or sell, participate in seminars, and discussing financial matters with executives and evaluate annual reports.

A Researcher is a professional who is responsible for collecting data and information by reviewing the literature and conducting experiments and surveys. He or she uses various methodological processes to provide accurate data and information that is utilised by academicians and other industry professionals. Here, we will discuss what is a researcher, the researcher's salary, types of researchers.

Welding Engineer

Welding Engineer Job Description: A Welding Engineer work involves managing welding projects and supervising welding teams. He or she is responsible for reviewing welding procedures, processes and documentation. A career as Welding Engineer involves conducting failure analyses and causes on welding issues. 

Transportation Planner

A career as Transportation Planner requires technical application of science and technology in engineering, particularly the concepts, equipment and technologies involved in the production of products and services. In fields like land use, infrastructure review, ecological standards and street design, he or she considers issues of health, environment and performance. A Transportation Planner assigns resources for implementing and designing programmes. He or she is responsible for assessing needs, preparing plans and forecasts and compliance with regulations.

Environmental Engineer

Individuals who opt for a career as an environmental engineer are construction professionals who utilise the skills and knowledge of biology, soil science, chemistry and the concept of engineering to design and develop projects that serve as solutions to various environmental problems. 

Safety Manager

A Safety Manager is a professional responsible for employee’s safety at work. He or she plans, implements and oversees the company’s employee safety. A Safety Manager ensures compliance and adherence to Occupational Health and Safety (OHS) guidelines.

Conservation Architect

A Conservation Architect is a professional responsible for conserving and restoring buildings or monuments having a historic value. He or she applies techniques to document and stabilise the object’s state without any further damage. A Conservation Architect restores the monuments and heritage buildings to bring them back to their original state.

Structural Engineer

A Structural Engineer designs buildings, bridges, and other related structures. He or she analyzes the structures and makes sure the structures are strong enough to be used by the people. A career as a Structural Engineer requires working in the construction process. It comes under the civil engineering discipline. A Structure Engineer creates structural models with the help of computer-aided design software. 

Highway Engineer

Highway Engineer Job Description:  A Highway Engineer is a civil engineer who specialises in planning and building thousands of miles of roads that support connectivity and allow transportation across the country. He or she ensures that traffic management schemes are effectively planned concerning economic sustainability and successful implementation.

Field Surveyor

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Orthotist and Prosthetist

Orthotists and Prosthetists are professionals who provide aid to patients with disabilities. They fix them to artificial limbs (prosthetics) and help them to regain stability. There are times when people lose their limbs in an accident. In some other occasions, they are born without a limb or orthopaedic impairment. Orthotists and prosthetists play a crucial role in their lives with fixing them to assistive devices and provide mobility.

Pathologist

A career in pathology in India is filled with several responsibilities as it is a medical branch and affects human lives. The demand for pathologists has been increasing over the past few years as people are getting more aware of different diseases. Not only that, but an increase in population and lifestyle changes have also contributed to the increase in a pathologist’s demand. The pathology careers provide an extremely huge number of opportunities and if you want to be a part of the medical field you can consider being a pathologist. If you want to know more about a career in pathology in India then continue reading this article.

Veterinary Doctor

Speech therapist, gynaecologist.

Gynaecology can be defined as the study of the female body. The job outlook for gynaecology is excellent since there is evergreen demand for one because of their responsibility of dealing with not only women’s health but also fertility and pregnancy issues. Although most women prefer to have a women obstetrician gynaecologist as their doctor, men also explore a career as a gynaecologist and there are ample amounts of male doctors in the field who are gynaecologists and aid women during delivery and childbirth. 

Audiologist

The audiologist career involves audiology professionals who are responsible to treat hearing loss and proactively preventing the relevant damage. Individuals who opt for a career as an audiologist use various testing strategies with the aim to determine if someone has a normal sensitivity to sounds or not. After the identification of hearing loss, a hearing doctor is required to determine which sections of the hearing are affected, to what extent they are affected, and where the wound causing the hearing loss is found. As soon as the hearing loss is identified, the patients are provided with recommendations for interventions and rehabilitation such as hearing aids, cochlear implants, and appropriate medical referrals. While audiology is a branch of science that studies and researches hearing, balance, and related disorders.

An oncologist is a specialised doctor responsible for providing medical care to patients diagnosed with cancer. He or she uses several therapies to control the cancer and its effect on the human body such as chemotherapy, immunotherapy, radiation therapy and biopsy. An oncologist designs a treatment plan based on a pathology report after diagnosing the type of cancer and where it is spreading inside the body.

Are you searching for an ‘Anatomist job description’? An Anatomist is a research professional who applies the laws of biological science to determine the ability of bodies of various living organisms including animals and humans to regenerate the damaged or destroyed organs. If you want to know what does an anatomist do, then read the entire article, where we will answer all your questions.

For an individual who opts for a career as an actor, the primary responsibility is to completely speak to the character he or she is playing and to persuade the crowd that the character is genuine by connecting with them and bringing them into the story. This applies to significant roles and littler parts, as all roles join to make an effective creation. Here in this article, we will discuss how to become an actor in India, actor exams, actor salary in India, and actor jobs. 

Individuals who opt for a career as acrobats create and direct original routines for themselves, in addition to developing interpretations of existing routines. The work of circus acrobats can be seen in a variety of performance settings, including circus, reality shows, sports events like the Olympics, movies and commercials. Individuals who opt for a career as acrobats must be prepared to face rejections and intermittent periods of work. The creativity of acrobats may extend to other aspects of the performance. For example, acrobats in the circus may work with gym trainers, celebrities or collaborate with other professionals to enhance such performance elements as costume and or maybe at the teaching end of the career.

Video Game Designer

Career as a video game designer is filled with excitement as well as responsibilities. A video game designer is someone who is involved in the process of creating a game from day one. He or she is responsible for fulfilling duties like designing the character of the game, the several levels involved, plot, art and similar other elements. Individuals who opt for a career as a video game designer may also write the codes for the game using different programming languages.

Depending on the video game designer job description and experience they may also have to lead a team and do the early testing of the game in order to suggest changes and find loopholes.

Radio Jockey

Radio Jockey is an exciting, promising career and a great challenge for music lovers. If you are really interested in a career as radio jockey, then it is very important for an RJ to have an automatic, fun, and friendly personality. If you want to get a job done in this field, a strong command of the language and a good voice are always good things. Apart from this, in order to be a good radio jockey, you will also listen to good radio jockeys so that you can understand their style and later make your own by practicing.

A career as radio jockey has a lot to offer to deserving candidates. If you want to know more about a career as radio jockey, and how to become a radio jockey then continue reading the article.

Choreographer

The word “choreography" actually comes from Greek words that mean “dance writing." Individuals who opt for a career as a choreographer create and direct original dances, in addition to developing interpretations of existing dances. A Choreographer dances and utilises his or her creativity in other aspects of dance performance. For example, he or she may work with the music director to select music or collaborate with other famous choreographers to enhance such performance elements as lighting, costume and set design.

Social Media Manager

A career as social media manager involves implementing the company’s or brand’s marketing plan across all social media channels. Social media managers help in building or improving a brand’s or a company’s website traffic, build brand awareness, create and implement marketing and brand strategy. Social media managers are key to important social communication as well.

Photographer

Photography is considered both a science and an art, an artistic means of expression in which the camera replaces the pen. In a career as a photographer, an individual is hired to capture the moments of public and private events, such as press conferences or weddings, or may also work inside a studio, where people go to get their picture clicked. Photography is divided into many streams each generating numerous career opportunities in photography. With the boom in advertising, media, and the fashion industry, photography has emerged as a lucrative and thrilling career option for many Indian youths.

An individual who is pursuing a career as a producer is responsible for managing the business aspects of production. They are involved in each aspect of production from its inception to deception. Famous movie producers review the script, recommend changes and visualise the story. 

They are responsible for overseeing the finance involved in the project and distributing the film for broadcasting on various platforms. A career as a producer is quite fulfilling as well as exhaustive in terms of playing different roles in order for a production to be successful. Famous movie producers are responsible for hiring creative and technical personnel on contract basis.

Copy Writer

In a career as a copywriter, one has to consult with the client and understand the brief well. A career as a copywriter has a lot to offer to deserving candidates. Several new mediums of advertising are opening therefore making it a lucrative career choice. Students can pursue various copywriter courses such as Journalism , Advertising , Marketing Management . Here, we have discussed how to become a freelance copywriter, copywriter career path, how to become a copywriter in India, and copywriting career outlook. 

In a career as a vlogger, one generally works for himself or herself. However, once an individual has gained viewership there are several brands and companies that approach them for paid collaboration. It is one of those fields where an individual can earn well while following his or her passion. 

Ever since internet costs got reduced the viewership for these types of content has increased on a large scale. Therefore, a career as a vlogger has a lot to offer. If you want to know more about the Vlogger eligibility, roles and responsibilities then continue reading the article. 

For publishing books, newspapers, magazines and digital material, editorial and commercial strategies are set by publishers. Individuals in publishing career paths make choices about the markets their businesses will reach and the type of content that their audience will be served. Individuals in book publisher careers collaborate with editorial staff, designers, authors, and freelance contributors who develop and manage the creation of content.

Careers in journalism are filled with excitement as well as responsibilities. One cannot afford to miss out on the details. As it is the small details that provide insights into a story. Depending on those insights a journalist goes about writing a news article. A journalism career can be stressful at times but if you are someone who is passionate about it then it is the right choice for you. If you want to know more about the media field and journalist career then continue reading this article.

Individuals in the editor career path is an unsung hero of the news industry who polishes the language of the news stories provided by stringers, reporters, copywriters and content writers and also news agencies. Individuals who opt for a career as an editor make it more persuasive, concise and clear for readers. In this article, we will discuss the details of the editor's career path such as how to become an editor in India, editor salary in India and editor skills and qualities.

Individuals who opt for a career as a reporter may often be at work on national holidays and festivities. He or she pitches various story ideas and covers news stories in risky situations. Students can pursue a BMC (Bachelor of Mass Communication) , B.M.M. (Bachelor of Mass Media) , or  MAJMC (MA in Journalism and Mass Communication) to become a reporter. While we sit at home reporters travel to locations to collect information that carries a news value.  

Corporate Executive

Are you searching for a Corporate Executive job description? A Corporate Executive role comes with administrative duties. He or she provides support to the leadership of the organisation. A Corporate Executive fulfils the business purpose and ensures its financial stability. In this article, we are going to discuss how to become corporate executive.

Multimedia Specialist

A multimedia specialist is a media professional who creates, audio, videos, graphic image files, computer animations for multimedia applications. He or she is responsible for planning, producing, and maintaining websites and applications. 

Quality Controller

A quality controller plays a crucial role in an organisation. He or she is responsible for performing quality checks on manufactured products. He or she identifies the defects in a product and rejects the product. 

A quality controller records detailed information about products with defects and sends it to the supervisor or plant manager to take necessary actions to improve the production process.

Production Manager

A QA Lead is in charge of the QA Team. The role of QA Lead comes with the responsibility of assessing services and products in order to determine that he or she meets the quality standards. He or she develops, implements and manages test plans. 

Process Development Engineer

The Process Development Engineers design, implement, manufacture, mine, and other production systems using technical knowledge and expertise in the industry. They use computer modeling software to test technologies and machinery. An individual who is opting career as Process Development Engineer is responsible for developing cost-effective and efficient processes. They also monitor the production process and ensure it functions smoothly and efficiently.

AWS Solution Architect

An AWS Solution Architect is someone who specializes in developing and implementing cloud computing systems. He or she has a good understanding of the various aspects of cloud computing and can confidently deploy and manage their systems. He or she troubleshoots the issues and evaluates the risk from the third party. 

Azure Administrator

An Azure Administrator is a professional responsible for implementing, monitoring, and maintaining Azure Solutions. He or she manages cloud infrastructure service instances and various cloud servers as well as sets up public and private cloud systems. 

Computer Programmer

Careers in computer programming primarily refer to the systematic act of writing code and moreover include wider computer science areas. The word 'programmer' or 'coder' has entered into practice with the growing number of newly self-taught tech enthusiasts. Computer programming careers involve the use of designs created by software developers and engineers and transforming them into commands that can be implemented by computers. These commands result in regular usage of social media sites, word-processing applications and browsers.

Information Security Manager

Individuals in the information security manager career path involves in overseeing and controlling all aspects of computer security. The IT security manager job description includes planning and carrying out security measures to protect the business data and information from corruption, theft, unauthorised access, and deliberate attack 

ITSM Manager

Automation test engineer.

An Automation Test Engineer job involves executing automated test scripts. He or she identifies the project’s problems and troubleshoots them. The role involves documenting the defect using management tools. He or she works with the application team in order to resolve any issues arising during the testing process. 

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Short Speech on Computer in English for Students and Children

3 minute speech on computer for school and college students.

Respected Principal, teachers and my dear classmates. A wonderful morning to all of you. Today we all have gathered here to celebrate this day, I would like to speak a few words on – ‘ Computer ’.

Needless to say how the computer has become an important part of our everyday life. Can we imagine our lives without it? I am sure the answer will be no!

Offices, schools, hospitals, governmental organizations, and non- governmental organizations, all are incomplete without it. Our work whether its school homework or office work or mother’s household work, all is dependent on the computer.

It has various uses. The medical field uses a computer to diagnose diseases. So far, they are able to find a cure for various diseases due to this computer. Even in the field of research, computers have brought a lot of changes. Whether its scientific research, social research, or space research, computers have helped in all of them. They have helped to keep a check on the environment, society, and space.

Computers have also contributed to the most important sector of a country, i.e, defense. It helps the country’s security agencies to detect a threat that can be harmful in the future. The defense industry also uses to keep surveillance on our enemy.

A computer has many advantages, as I mentioned earlier but there is nothing in this world which has no disadvantages. Even computer which has become so important for us has disadvantaged such as hackers can steal the data and release it on the internet. Anyone can access this data.

Apart from this threat, there are other threats too. Such as threats like viruses, spams, bugs, etc. It has become an addiction too for many people. Even students spend a lot of their time sitting in front of computer screen playing games and watching movies.

We need to remind ourselves that excess of everything is bad. We should try and limit its use as it’s excessive use can be harmful to our eyes, back, brain and can lead to various problems too.

In the end, I would like to add that it is a boon and we can stop it to become bane if we use it cautiously. Thank you for lending me your ears.

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Speech on Computer (Short & Long Speech) For Students

Speech on computer, introduction.

A very good morning to one and all present over here . Respected guests and my dear friends , today I will be giving speech on the topic “COMPUTER”

Computer is an electronic device. First computer was invented by Charles Babbage in 1822. It was a great invention for modern technology.  He invented digital computer known as analytical engine. At that time computers were only meant for calculations. The size of computer at that time was eleven feet long and seven feet high with 8,000 parts of weigh five tons i.e it covers a whole room. Later, as the time passed the size of computer decreased due to use of transistors instead of valve. A computer runs on a three step cycle- input, process and output. It consist of several parts such as CPU, motherboard, monitor, keyboard, RAM, hard disk drive, mouse, power supply, ROM etc. Each and every partof computer has different functions such as monitor is used to display all the data, CPU (central processing unit) is the  brain of  computer because it consist of an arithmetic logic unit and a control unit, motherboard control all computer circuits and it is an important part of computer and RAM is used to store short term memory. The computer parts are divided into two devices i.e. input (eg- keyboard, mouse) and output devices (eg- monitor, printer).  Computer are classified into two categories- by architecture and by size and purpose. In this  architecture computer includes analog computer, digital computer, von Neumann , Harvard computer and hybrid computer. But in daily use we generally use second type of computer that is size and purpose computer. This type of computer includes mini computer, mainframe computer, microcomputer, supercomputer. The microcomputer is a single user computer with less speed and low capacity of storage. For eg- personal digital assistant, tablet, desktop computers. In minicomputers, it has power less than mainframe but more than micro computer. The mainframe computer store large amount of data and can be used in banks, universities. The last one is supercomputer, it has enormous storage capacity with fastest speed among all types of computer. Computer are of great use such as for calculation, communication( messaging, video call), playing games, writing, making animation, audio video and photo editing, entertainment, making powerpoint slide, Notepad. Computers are used in the field such as defense, industry, education, banking, business, government, hospital, research field. Now a days, there is a large demand of software engineers as all the jobs are carried out by computers only. The skills which we can learn from computer is java, python, C++ , animations and  coding. Some famous brands of computer are Hewlett-Packard (HP), Sony, Asus, Samsung, Lenovo,  dell, apple & intex. But there are some disadvantages of computers such as bad effect on health ( especially eyes, brain and spinal cord), misuse, wastage of time by scrolling down a site, lots of distractions, cyber crime, loss of potential, limited learning,  increases waste, polluting the environment, reduces the job opportunities.  Other threats which incudes viruses, spams and bugs.

Today, the world is more depended on computer and in future computer can replace human being. It is a boon, don’t let it to become bane. Artificial intelligence is taking over the world, which is not very fortunate for the growing population. Computers should only be used where they are needed, and shouldn’t be used to replace the human workforce. Let’s use this as a resource.

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• Speech on Technology

Technology in This Generation

We are in a generation, where technology has surrounded us from all sides. Our everyday life runs on the use of technology, be it in the form of an alarm clock or a table lamp. Technology has been an important part of our daily lives. Therefore, it is important for the students to be familiar with the term technology. Therefore, we have provided a long speech on technology for students of all age groups. There is also a short speech and a 10 lines speech given in this article.

Long Speech on Technology

A warm welcome to everyone gathered here today. I am here to deliver a speech on technology which has taken a tremendous role in our day to day life. We all are in a generation where everything is dependent on technology. Let’s understand what technology is through the lens of Science. 

Technology comes in the form of tangible and intangible properties by exerting physical and mental force to achieve something that adds value. For example, a mobile phone is tangible, and the network connection used by the phone is intangible. Technology has taken its place as indispensable, wherein it has resulted in economic benefits, better health care, time-saving, and better lifestyle.

Due to technology, we have a significant amount of knowledge to improve our lives and solve problems. We can get our work done efficiently and effectively. As long as you know how to access technology, it can be used and proves to benefit people of all ages greatly. Technology is constantly being modified and upgraded every passing year. 

The evolution of technology has made it possible to achieve lots in less time. Technology has given tools and machines to be used to solve problems around the world. There has been a complete transformation in the way we do things because of contributions from scientific technology. We can achieve more tasks while saving our time and hence in a better place than our previous generation. 

Right from the ringing of the morning alarm to switching off the fan, everything runs behind the technology. Even the microphone that I am using is an innovation of technology and thus the list continues. With several inventions of hi-tech products, our daily needs are available on a screen at our fingertips. These innovations and technologies have made our lives a lot easier. Everything can be done at the comfort of your home within a couple of hours or so. These technologies have not only helped us in the digital platform but have also given us innovations in the field of medical, educational, industrial as well as in agricultural sectors. If we go back to the older generations, it would take days to get any things solved, even if there were not many treatments for several diseases. 

But today with the innovations of technology, many diseases can be treated and diagnosed within a shorter period of time. The relationship between humans and technology has continued for ages and has given rise to many innovations. It has made it easier for us to handle our daily chores starting from home, office, schools and kitchen needs. It has made available basic necessities and safer living spaces. We can sit at home comfortably and make transactions through the use of online banking. Online shopping, video calling, and attending video lectures on the phone have all been possible due to the invention of the internet. 

People in the past would write letters to communicate with one another, and today due to technology, traditional letters have been replaced by emails and mobile phones. These features are the essential gifts of technology. Everything is just at our fingertips, right from turning on the lights to doing our laundry. The whole world runs on technology and hence, we are solely dependent on it. But everything has its pros and cons. While the benefits of technology are immense, it also comes with some negative effects and possibly irreversible damages to humanity and our planet. 

We have become so dependent on technology that we often avoid doing things on our own. It as a result makes us lazy and physically inactive. This has also led to several health issues such as obesity and heart diseases. We prefer booking a cab online rather than walking a few kilometres. Technology has increased screen time, and thus, children are no longer used to playing in the playgrounds but are rather found spending hours on their phones playing video games. This has eroded children’s creativity, intelligence, and memory. No doubt, technology is a very essential part of our life, but we should not be totally dependent on it. We should practise being more fit and do regular activities on our own to maintain a healthy lifestyle.

The other aspects that have been badly affected us are that since technology replaced human interference, is unemployment. Social media platforms like Instagram, Facebook, Twitter, etc., were meant to connect people and increase our community circle. Still, it has made people all the more lonely, with cases of depression on the rise amongst the youth. 

There are several controversies around the way world leaders have used technology in defence and industrialisation under the banner of development and advancements. The side effects of technology have resulted in pollution, climate change, forest fires, extreme storms, cyclones, impure air, global warming, land area getting reduced and natural resources getting extinct. It’s time we change our outlook towards selfish technology and bring about responsible technology. Every nation needs to set aside budgets to come up with sustainable technological developments. 

As students, we should develop creative problem solving using critical thinking to bring clean technology into our world. As we improve our nation, we must think of our future for a greener and cleaner tomorrow. You would be glad to know that several initiatives have been initiated to bring awareness amongst children and youth to invent cleaner technology. 

For example, 15-year-old Vinisha Umashankar invented a solar ironing cart and has been awarded the Earth Shot Prize by the Royal Foundation of the duke and duchess of Cambridge and honoured to speak at the COP26 climate change conference in Glasgow, Scotland. Her invention should be an inspiration to each one of us to pursue clean technology.

The top five technologically advanced countries are Japan, America, Germany, China and South Korea. We Indians will make our mark on this list someday. Technology has a vital role in our lives but lets us be mindful that we control technology and that technology doesn’t control us. Technology is a tool to elevate humanity and is not meant to be a self-destroying mechanism under the pretext of economic development. Lastly, I would like to conclude my speech by saying that technology is a boon for our society but we should use it in a productive way. 

A Short Speech on Technology

A warm greeting to everyone present here. Today I am here to talk about technology and how it has gifted us with various innovations. Technology as we know it is the application of scientific ideas to develop a machine or a device for serving the needs of humans. We, human beings, are completely dependent on technology in our daily life. We have used technology in every aspect of our life starting from household needs, schools, offices, communication and entertainment. Our life has been more comfortable due to the use of technology. We are in a much better and comfortable position as compared to our older generation. This is possible because of various contributions and innovations made in the field of technology. Everything has been made easily accessible for us at our fingertips right from buying a thing online to making any banking transaction. It has also led to the invention of the internet which gave us access to search for any information on google. But there are also some disadvantages. Relying too much on technology has made us physically lazy and unhealthy due to the lack of any physical activity. Children have become more prone to video games and social media which have led to obesity and depression. Since they are no longer used to playing outside and socialising, they often feel isolated. Therefore, we must not totally be dependent on technology and should try using it in a productive way.

10 Lines Speech on Technology

Technology has taken an important place in our lives and is considered an asset for our daily needs.

The world around us is totally dependent on technology, thus, making our lives easier.

The innovation of phones, televisions and laptops has digitally served the purpose of entertainment today.

Technology has not only helped us digitally but has also led to various innovations in the field of medical science.

Earlier it took years to diagnose and treat any particular disease, but today with the help of technology it has led to the early diagnosis of several diseases.

We, in this generation, like to do things sitting at our own comfort within a short period of time. This thing has been made possible by technology.

All our daily activities such as banking, shopping, entertainment, learning and communication can be done on a digital platform just by a click on our phone screen.

Although all these gifts of technology are really making our lives faster and easier, it too has got several disadvantages.

Since we all are highly dependent on technology, it has reduced our daily physical activity. We no longer put effort to do anything on our own as everything is available at a minute's click.

Children nowadays are more addicted to online video games rather than playing outside in the playground. These habits make them more physically inactive.

FAQs on Speech on Technology

1. Which kind of technology is the most widely used nowadays?

Artificial Intelligence (AI) is the field of technology that is being used the most nowadays and is expected to grow even more even in the future. With AI being adopted in numerous sectors and industries and continuously more research being done on it, it will not be long before we see more forms of AI in our daily lives.

2. What is the biggest area of concern with using technology nowadays?

Protection of the data you have online is the biggest area of concern. With hacking and cyberattacks being so common, it is important for everyone to ensure they do not post sensitive data online and be cautious when sharing information with others.

Importance of computers

Today is the world of computers as every field is dependent on it. From the business owners to the working professionals, students and adults everyone in some way or the other use the computers in their daily lives. The computers have not only enhanced the efficiency of the work but offer top notch results as well. This is the reason that computers have become an important part of our lives and it is difficult to live without them.

One cannot deny the importance of computers as different sectors use it for different purposes. Like the corporate world relies on the computers for managing their work, students use it to complete their assignments and projects; banking sector uses to handle the accounts of their customers and lots more. So you can say that there is no sector which is untouched by the influence of the computers.

Computers have emerged as one of the best technologies which have not only reduced the manual burden but improved the work quality as well. That is why the computers are so much in demand and utilized to the fullest. So let us see how computers are becoming more and more essential for us.

Workplace: Gone are the days when the work was done manually but today computers are being employed to accomplish the different purposes like managing the accounts, creating a database, storing the necessary information etc. The computers have paved the way for the traditional options as it is more secure and efficient too. The improvements in the technology enable us to access the information wherever we are. This has definitely proved as an advantage for the people and that is why computers have proved beneficial in this concern.

With computers being connected to the internet, its utility has increased a lot. There are lots of offices whose work is done entirely through the internet. Thus they very much rely on the computers and the internet to complete their daily tasks. Several financial transactions are also possible through the computers and the internet, so it can be said that our lives are surrounded by both these things only.

In the field of entertainment: Nowadays the computers have been replaced with a more portable device like laptops and other options including tablets etc. As these are light weighted, carrying them with you is quite easy. Thus with the help of the computers, you can watch movies, listen to songs, enjoy videos and do everything you like. Even while you are traveling, you have the access to all this stuff. If you connect your laptops to the internet you can enjoy live entertainment like watch movies online, download songs, watch videos and much more. Thus computer offers on the go entertainment and this is something that has changed our lives.

In the field of education: Computers are not only useful for the kids but for the teachers as well. On one hand, where computers can help the children, in the long run, the teachers can be a benefit in preparing the presentations and offering a new teaching experience to the kids. The process of learning is enhanced through computers and it is simple to keep the kids engaged. Also preparing documents and test papers can be done via the internet. So in the field of education, the computers are playing a role in improving the overall teaching methodology and learning experience of the students.

For personal use: Today everyone home has a computer or laptop which they use for personal purposes. It can be for playing games or doing other activities. Even the kids are accessing the computers in their home and are learning new things. It is surely a great step because the knowledge of computers is necessary to move ahead and if one gets the opportunity to learn, nothing can be better than this.

The only thing to ensure is the right usage if kids are using the computer. Make sure that there is someone along with the kids to monitor the type of content they are viewing or the activities they are involved in. Thus from the above information, it is very clear that computers have become a vital part of everyone’s life. It not only offers you entertainment but accomplishes your work as well. You can look forward to better outcomes and more refined results which are not possible manually. This is the reason that every field or sector is using computers for different purposes so that the results are top class. So enjoy the wonders of computers and move ahead with the new technologies.

5 thoughts on “ Importance of computers ”

Is their more importance of computer

Nice i like it

Well written!

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Bringing a new voice to genius—mitalk, the calltext 5010, and stephen hawking’s wheelchair, by chris garcia | march 26, 2018.

Stephen Hawking, 1942−2018. Image: howitworksdaily.com .

On March 13, 2018, the world lost one of the greatest theoretical physicists who ever lived. Stephen Hawking had a profound effect on our understanding of how the universe works and the rare talent to bring these theories to the masses. Without Hawking, it’s doubtful that so many would be aware of concepts such as black holes, cosmic inflation, or quantum dynamics. In addition to his far-reaching research, he was a popular science writer and perhaps the most widely recognized figure representing the sciences in the period between the Sagan and DeGrasse-Tyson epochs. His book, A Brief History of Time , was a smash hit, one of the most widely read scientific books ever written. He was also one of the most widely awarded figures in history, ascending in 1979 to the Lucasian Professorship in Mathematics at Cambridge, the same position held by Sir Isaac Newton and Charles Babbage. He was elected Fellow of the Royal Society in 1974 and was later made a Commander of the Order of the British Empire in 1982. In 2009 Hawking was awarded the US Presidential Medal of Freedom by President Obama. All that, and he appeared in episodes of Star Trek: The Next Generation , The Big Bang Theory , and as a character on The Simpsons.

Hawking suffered from amyotrophic lateral sclerosis, also known as ALS or Lou Gehrig’s disease. The disease would eventually paralyze him, leaving him confined to a wheelchair for more than 50 years. A bout of pneumonia in the mid-1980s made him unable to speak on his own. For such a public figure, this was a significant difficulty, one that led Hawking to a long-lasting and now widely recognized solution: voice synthesis.

Research into voice synthesis actually predates electronic computing. The legend of the “brazen head,” a magical or mechanical bust that could speak simple words, dates back to at least the 11th century, while Wolfgang von Kempelen’s speaking machine mimicked speech as far back as 1769 using a bellows system. Work in the 19th century attempted to mimic speech through a variety of methods using bellows and percussive elements. It was through Bell Labs’ Vocoder that electronic speech synthesis first became possible. Using the Vocoder concept he had begun working on in 1928, Homer Dudley developed the Voder, a keyboard-based voice synthesis system he displayed at the 1939 World’s Fair in New York.

He Saw the Cat album cover

Throughout the 1950s and 1960s, Bell Labs remained a leading institution for research into computer speech. Max Matthews and his team developed a speech system later used to sing the iconic “Daisy Belle” for Stanley Kubrick’s 2001: A Space Odyssey . They even released a record of much of their speech synthesis work called He Saw the Cat . By the late 1970s, miniaturization and the microprocessor led to new smaller, portable speech synthesis systems. Dr. Ray Kurzweil developed his Kurzweil Reading System, which became popular in organizations providing services for the blind, though it was not widely adopted for individual use as the cost and technical demands of the system were very high.

At MIT, Senior Researcher Dennis Klatt had been working on speech synthesis techniques since the mid-1960s. He was a student of the history of artificial speech, collected many recordings of early systems, and in parallel, developed his own. His research focused on creating synthesized voices that felt more natural than those that researchers at Bell Labs and other institutions had created. While earlier voices had been intelligible, they sounded “electronic,” and the synthesis of the female voice in particular never yielded strong results. Klatt spent a great deal of time looking into not only how speech is made by the body, but also how it is perceived by the listener. This is an important point, because whether or not the user can understand the words and phrases they are using, it is equally important that the listener is able to interact with those sounds in a natural way to allow for effective communication.

DECtalk advertisement, 1984

Klatt developed a source filter algorithm that he called both KlattTalk and MITalk (pronounced “My-Talk”), which was then licensed to Digital Equipment Corporation (DEC) , who released it as DECtalk. Early DECtalk marketing targeted corporations, and even the first ads noted its potential for use by the vision or speech impaired. “It can give a vision-impaired person an effective, economical way to work with computers. And it can give a speech-impaired person a way to verbalize his or her thoughts in person or over the phone.” Groups like the National Weather Service and National Institute for the Blind, as well as several phone companies, began using DECtalk in various applications. DECtalk could produce eight different voices, with “Perfect Paul,” based around Klatt’s own voice, the default for the initial DECtalk terminals.

By the late 1970s, ALS had taken much of Hawking’s ability to speak clearly, and treatment for pneumonia in 1985 made it impossible for him to speak on his own. Initially, Hawking and his team developed a partner-assisted method to communicate. He would indicate letters on a spelling card by raising his eyebrows. This was slow and inexact, and considering the subjects Hawking spoke on regularly, was not practical.

In 1986, Hawking was given a software package called the “Equalizer,” which had been developed by Walter Woltosz as a way to assist his mother-in-law, who suffered from ALS, in her communication. The initial version of the system allowed Hawking to communicate using his thumbs to enter simple commands, selecting words from a database of roughly 3,000 words and phrases, or selecting letters to spell words not contained in the database.

At first, the method required a desktop Apple II computer, and later the husband of one of his caregivers developed a way to bring the computer on-board his wheelchair. “I can communicate better now than before I lost my voice,” Hawking said.

The voice synthesis was handled by a Speech Plus CallText 5010 text-to-speech synthesizer built into the back of Hawking’s wheelchair. The voice used by the CallText was based around Klatt’s MITalk, just like DECtalk, but had only a single voice and had been modified and improved by Speech Plus over a 10-year span. A crisp, American-accented voice, it was a clear and well-paced speech pattern that Hawking liked, despite the availability of other voices and synthesis options as time went on.

Stephen Hawking interacting with the ACAT system. Image: itpro.co.uk .

Over the years, Hawking began to lose his ability to control his thumbs. This posed a serious challenge, as it made it incredibly difficult, and later impossible, to use the system that had been developed for him in the 1980s. In 1997, he turned to Intel to help develop a new wheelchair and voice control system. The new system was ACAT—Assistive Context-Aware Toolkit. To allow Hawking to speak, ACAT used a tablet PC connected to the chair and an infrared sensor located in his glasses. The sensor would detect minute movements of a cheek muscle, allowing him to select words, letters, and phrases using a predictive text method developed by the company SwiftKey. The system allowed Hawking to continue with his work and even make Skype calls. Periodic upgrades to the chair helped compensate for the increasing levels of difficulty Hawking had with muscle control, but one thing stayed the same. His voice.

Until nearly the end of his life, Hawking’s preferred voice was the one synthesized by the CallText 5010. It was only in 2014 that Hawking’s original CallText 5010 synthesizers needed to be replaced. New techniques and voices were tried, but Hawking vetoed their use. The reason—Hawking liked the way the CallText sounded. Almost two decades after Speech Plus had gone out of business, he wanted a replacement. Hawking’s assistants contacted Eric Dorsey, who had worked on the original CallText system, to resurrect the original. When that proved too difficult, a replacement was created. The team created a software emulation of the CallText 5010 based around a Raspberry Pi computer. The voice may have sounded slightly different due to the speakers and other hardware being used to pronounce the actual synthesized sounds, but it was the CallText voice, Dennis Klatt’s synthesized voice, that brought sound back to Stephen Hawking’s genius.

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About The Author

Chris Garcia joined the Computer History Museum in 1999. As Curator, Chris provides information on artifacts, develops content for exhibits, assists in donation review, gives talks, tours and writes articles for CORE—the official publication of the Museum.

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How Do Computers Understand Speech?

By arika okrent | nov 27, 2012.

More and more, we can get computers to do things for us by talking to them. A computer can call your mother when you tell it to, find you a pizza place when you ask for one, or write out an email that you dictate. Sometimes the computer gets it wrong, but a lot of the time it gets it right, which is amazing when you think about what a computer has to do to turn human speech into written words: turn tiny changes in air pressure into language. Computer speech recognition is very complicated and has a long history of development , but here, condensed for you, are the 7 basic things a computer has to do to understand speech.

1. Turn the movement of air molecules into numbers.

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Sound comes into your ear or a microphone as changes in air pressure, a continuous sound wave. The computer records a measurement of that wave at one point in time, stores it, and then measures it again. If it waits too long between measurements, it will miss important changes in the wave. To get a good approximation of a speech wave, it has to take a measurement at least 8000 times a second, but it works better if it takes one 44,100 times a second. This process is otherwise known as digitization at 8kHz or 44.1kHz.

2. Figure out which parts of the sound wave are speech.

When the computer takes measurements of air pressure changes, it doesn't know which ones are caused by speech, and which are caused by passing cars, rustling fabric, or the hum of hard drives. A variety of mathematical operations are performed on the digitized sound wave to filter out the stuff that doesn't look like what we expect from speech. We kind of know what to expect from speech, but not enough to make separating the noise out an easy task.

3. Pick out the parts of the sound wave that help tell speech sounds apart.

A sound wave from speech is actually a very complex mix of multiple waves coming at different frequencies. The particular frequencies—how they change, and how strongly those frequencies are coming through—matter a lot in telling the difference between, say, an "ah" sound and an "ee" sound. More mathematical operations transform the complex wave into a numerical representation of the important features.

4. Look at small chunks of the digitized sound one after the other and guess what speech sound each chunk shows.

There are about 40 speech sounds, or phonemes, in English. The computer has a general idea of what each of them should look like because it has been trained on a bunch of examples. But not only do the characteristics of these phonemes vary with different speaker accents, they change depending on the phonemes next to them—the 't' in "star" looks different than the 't' in "city." The computer must have a model of each phoneme in a bunch of different contexts for it to make a good guess.

5. Guess possible words that could be made up of those phonemes.

The computer has a big list of words that includes the different ways they can be pronounced. It makes guesses about what words are being spoken by splitting up the string of phonemes into strings of permissible words. If it sees the sequence "hang ten," it shouldn't split it into "hey, ngten!" because "ngten" won't find a good match in the dictionary.

6. Determine the most likely sequence of words based on how people actually talk.

There are no word breaks in the speech stream. The computer has to figure out where to put them by finding strings of phonemes that match valid words. There can be multiple guesses about what English words make up the speech stream, but not all of them will make good sequences of words. "What do cats like for breakfast?" could be just as good a guess as "water gaslight four brick vast?" if words are the only consideration. The computer applies models of how likely one word is to follow the next in order to determine which word string is the best guess. Some systems also take into account other information, like dependencies between words that are not next to each other. But the more information you want to use, the more processing power you need.

7. Take action

Once the computer has decided which guesses to go with, it can take action. In the case of dictation software, it will print the guess to the screen. In the case of a customer service phone line, it will try to match the guess to one of its pre-set menu items. In the case of Siri, it will make a call, look up something on the Internet, or try to come up with an answer to match the guess. As anyone who has used speech recognition software knows, mistakes happen. All the complicated statistics and mathematical transformations might not prevent "recognize speech" from coming out as " wreck a nice beach ," but for a computer to pluck either one of those phrases out of the air is still pretty incredible.

The technology that gave Stephen Hawking a voice should be accessible to all who need it

Professor of Speech Pathology, University of Technology Sydney

Disclosure statement

Bronwyn Hemsley is an Editor-in-Chief of the international journal 'Augmentative and Alternative Communication', a role for which she receives an annual honorarium, and member of the research committee of the International Society for Augmentative and Alternative Communication (ISAAC). Her research on the use of communication technologies for people with communication disability has been funded by the Australian Research Council and the National Health and Medical Research Council. She is a Fellow of Speech Pathology Australia and Fellow of ISAAC International.

University of Technology Sydney provides funding as a founding partner of The Conversation AU.

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Stephen Hawking was one of the most prominent people in history to use a high-tech communication aid known as augmentative and alternative communication (AAC) .

His death comes in the year of the 70th Anniversary of the Declaration of Human Rights . Over the course of his adult life, Hawking came to represent the epitome of what effective communication with AAC systems really means: gaining access to the human right of communication enshrined in Article 19 of the Universal Declaration of Human Rights .

Today, many Australians who need AAC still lack access to the technology and the support they need to use it. It’s time for that to change.

How augmentative and alternative communication works

To most people who can speak, AAC systems are a bit of a mystery – it’s not always clear how the person using it is controlling the system. Indeed, people’s fascination with how a speech device works often overtakes their attention to what the person is actually saying.

AAC includes sign and gesture systems, communication boards, speech-generating devices, mobile phones with apps, and even emojis and social media . Ultimately it works not only through the interaction of the user with their device, but also through their interactions with communication partners.

Read more: Stephen Hawking as accidental ambassador for assistive technologies

Some types of AAC don’t involve technology at all, but use the person’s body, such as sign or gesture systems. Some AAC systems are non-electronic , like communication boards, books, or wallets for people to point to or look at letters, words or phrases to communicate. Other types of AAC are known as “high-tech”, in that they involve electronic systems and computer-based technologies to both store and retrieve words for communication.

Apart from the time taken to compose a message, it can take hours to program what could be spoken using a communication aid – and many more to ensure that the desired words can be found just in time for communication.

Hawking used a switch to control software on a computer that enabled him to talk. This kind of switch allows users to scan through options shown on the screen until they reach the letter, word or message to select for the device to “speak”.

Realising the potential of people with communication disability

Hawking did not tend to use his platform in relation to disability , but when he did his words were significant. In writing the foreword to the World Report on Disability in 2011 , he highlighted the importance of people with disability having access to the equipment that they need, saying:

…we have a moral duty to remove the barriers to participation, and to invest sufficient funding and expertise to unlock the vast potential of people with disabilities.

Read more: A timeline of Stephen Hawking's remarkable life

A patron of the Motor Neurone Disease Association, Hawking inspired millions of people around the world with the condition. His lifetime achievement as a person who uses AAC was recognised by the International Society for Augmentative and Alternative Communication .

Although he hoped to be remembered more for his science than for his popular appearances on The Simpsons, his character delivered a vital line on communication rights and the need for AAC with a firm directive: “Silence. I don’t need anyone to talk for me except this voice box.”

His call to “look up at the stars”, should further compel AAC users and communication technologists to work together and reach for the stars in finding solutions for people who cannot rely on speech to communicate.

People who use AAC need to have a say in the design process

Hawking’s fame attracted the world’s best and brightest to work with him to solve problems around the use of communication technologies. But AAC systems still don’t stop people from “ slipping through the timestream ” of conversation. Communication using AAC systems is slow and effortful.

It can be hard to make a comment in a conversation – by the time the person has got the attention of other speakers and composed their message, the conversation has moved on, and the message is delivered “out of time”. It’s a puzzle to find systems that improve the timing and flow of talk, to match each user’s communication needs.

Read more: Listen to me: machines learn to understand how we speak

Even as communication tech advanced and Hawking’s distinct voice got an upgrade , he chose to keep his “ robotic drawl ”. Like the famous film critic Roger Ebert before him , he had the final say on his own vocal identity.

Hawking’s empowered story highlights the importance of designers not allowing ableist notions of an acceptable voice to restrict an AAC user’s self-expression. His stance also reflects the importance of people who use AAC co-designing AAC systems that reflect their own identity .

Making AAC accessible to all

Hawking knew his privileges in having access to the equipment and the social supports he needed to participate. Unfortunately, many people in Australia who need AAC lack access not only to the funds they need for the technology, but also to the professionals, such as speech pathologists, who know how to design and teach people how to use communication systems.

The Australian Bureau of Statistics estimates that as many as 1.2 million Australians have a communication disability. With roughly a quarter of all people with cerebral palsy or autism spectrum disorders being unable to rely on speech to communicate , it is vital that more is done to improve access to AAC worldwide.

Like all people who use AAC, Stephen Hawking was unique. It’s time to make communication systems like the one he used available for all who need it, so that they too can have their chance to shine.

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These experimental brain implants can restore speech to paralyzed patients.

Jon Hamilton

Pat Bennett takes part in a research session, using a brain-computer interface that helps translate her thoughts into speech. Steve Fisch/Stanford University hide caption

Pat Bennett takes part in a research session, using a brain-computer interface that helps translate her thoughts into speech.

For Pat Bennett, 68, every spoken word is a struggle.

Bennett has amyotrophic lateral sclerosis (ALS), a degenerative disease that has disabled the nerve cells controlling her vocal and facial muscles. As a result, her attempts to speak sound like a series of grunts.

But in a lab at Stanford University, an experimental brain-computer interface is able to transform Bennett's thoughts into easily intelligible sentences, like, "I am thirsty," and "bring my glasses here."

The system is one of two described in the journal Nature that use a direct connection to the brain to restore speech to a person who has lost that ability. One of the systems even simulates the user's own voice and offers a talking avatar on a computer screen.

Right now, the systems only work in the lab, and require wires that pass through the skull. But wireless, consumer-friendly versions are on the way, says Dr. Jaimie Henderson , a professor of neurosurgery at Stanford University whose lab created the system used by Bennett.

"This is an encouraging proof of concept," Henderson says. "I'm confident that within 5 or 10 years we'll see these systems actually showing up in people's homes."

In an editorial accompanying the Nature studies, Nick Ramsey, a cognitive neuroscientist at the Utrecht Brain Center, and Dr. Nathan Crone, a professor of neurology at Johns Hopkins University, write that "these systems show great promise in boosting the quality of life of individuals who have lost their voice as a result of paralyzing neurological injuries and diseases."

Neither scientists were involved in the new research.

Having an out-of-body experience? Blame this sausage-shaped piece of your brain

Thoughts with no voice.

The systems rely on brain circuits that become active when a person attempts to speak, or just thinks about speaking. Those circuits continue to function even when a disease or injury prevents the signals from reaching the muscles that produce speech.

"The brain is still representing that activity," Henderson says. "It just isn't getting past the blockage."

For Bennett, the woman with ALS, surgeons implanted tiny sensors in a brain area involved in speech.

The sensors are connected to wires that carry signals from her brain to a computer, which has learned to decode the patterns of brain activity Bennett produces when she attempts to make specific speech sounds, or phonemes.

That stream of phonemes is then processed by a program known as a language model.

"The language model is essentially a sophisticated auto-correct," Henderson says. "It takes all of those phonemes, which have been turned into words, and then decides which of those words are the most appropriate ones in context."

The language model has a vocabulary of 125,000 words, enough to say just about anything. And the entire system allows Bennett to produce more than 60 words a minute, which is about half the speed of a typical conversation.

Even so, the system is still an imperfect solution for Bennett.

"She's able to do a very good job with it over short stretches," Henderson says. "But eventually there are errors that creep in."

The system gets about one in four words wrong.

Want to understand your adolescent? Get to know their brain

An avatar that speaks.

A second system , using a slightly different approach, was developed by a team headed by Dr. Eddie Chang , a neurosurgeon at the University of California, San Francisco.

Instead of implanting electrodes in the brain, the team has been placing them on the brain's surface, beneath the skull.

In 2021, Chang's team reported that the approach allowed a man who'd had a stroke to produce text on a computer screen.

This time, they equipped a woman who'd had a stroke with an improved system and got "a lot better performance," Chang says.

She is able to produce more than 70 words a minute, compared to 15 words a minute for the previous patient who used the earlier system. And the computer allows her to speak with a voice that sounds like her own used to.

Perhaps most striking, the new system includes an avatar — a digital face that appears to speak as the woman remains silent and motionless, just thinking about the words she wants to say.

Those features make the new system much more engaging, Chang says.

"Hearing someone's voice and then seeing someone's face actually move when they speak," he says, "those are the things we gain from talking in person, as opposed to just texting."

Those features also help the new system offer more than just a way to communicate, Chang says.

"There is this aspect to it that is, to some degree, restoring identity and personhood."

When a brain injury impairs memory, a pulse of electricity may help

Scientists zap sleeping humans' brains with electricity to improve their memory

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Human–Computer Interaction with a Real-Time Speech Emotion Recognition with Ensembling Techniques 1D Convolution Neural Network and Attention

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Data are available publicly and cited in proper places in the text.

Emotions have a crucial function in the mental existence of humans. They are vital for identifying a person’s behaviour and mental condition. Speech Emotion Recognition (SER) is extracting a speaker’s emotional state from their speech signal. SER is a growing discipline in human–computer interaction, and it has recently attracted more significant interest. This is because there are not so many universal emotions; therefore, any intelligent system with enough computational capacity can educate itself to recognise them. However, the issue is that human speech is immensely diverse, making it difficult to create a single, standardised recipe for detecting hidden emotions. This work attempted to solve this research difficulty by combining a multilingual emotional dataset with building a more generalised and effective model for recognising human emotions. A two-step process was used to develop the model. The first stage involved the extraction of features, and the second stage involved the classification of the features that were extracted. ZCR, RMSE, and the renowned MFC coefficients were retrieved as features. Two proposed models, 1D CNN combined with LSTM and attention and a proprietary 2D CNN architecture, were used for classification. The outcomes demonstrated that the suggested 1D CNN with LSTM and attention performed better than the 2D CNN. For the EMO-DB, SAVEE, ANAD, and BAVED datasets, the model’s accuracy was 96.72%, 97.13%, 96.72%, and 88.39%, respectively. The model beat several earlier efforts on the same datasets, demonstrating the generality and efficacy of recognising multiple emotions from various languages.

1. Introduction

Emotion is a complex phenomenon that is influenced by numerous circumstances. Charles Darwin [ 1 ], one of the earliest scientists to study emotions, saw emotional expression as the last of behavioural patterns that had become obsolete owing to evolutionary change. In [ 2 ] theory of emotion was only a partial assertion and that feeling still serves an essential purpose; it is simply the nature of this purpose that has developed. Emotions are occasionally felt when something unexpected occurs, something to which evolution has not yet adapted, and in the circumstances such as these, emotional consequences start to take control. It is well-recognised that people’s emotional states can cause physical changes in their bodies. Emotions, for instance, may affect voice alterations [ 1 ]. Therefore, speech signals, which account for 38% of all emotional communication, can recognise and convey emotions [ 3 ]. The sound signals contain some elements that represent the speaker’s emotional state and those that correspond to the speaker and the speech. As a result, the fundamental idea behind emotion detection is examining the acoustic difference that arises while pronouncing the same thing in various emotional contexts [ 4 ]. Voice signals can be picked up without any device connected to the individual, even if alterations cannot be recognised without a portable medical instrument. Due to this, most studies on the subject have concentrated on automatically identifying emotions from auditory cues [ 5 ].

In human–computer interaction (HCI) and its applications, automatic emotion recognition is crucial since it can be a powerful feedback mechanism [ 6 , 7 ]. The main tools used in traditional HCI include the keyboard, mouse, screen, etc. It cannot comprehend and adjust to people’s emotions or moods; it just seeks convenience and precision. It is not easy to expect the computer to have the same intellect as people if it cannot recognise and convey emotions. Furthermore, it is challenging to anticipate that HCI will be genuinely harmonious and natural. People naturally expect computers to have emotional skills in the process of HCI since human interactions and communication are natural and emotional. The goal of affective computing is to give computers the capacity to perceive, comprehend, and produce a variety of emotional qualities similar to those found in humans. This will eventually allow computers to engage with humans in a way that is natural, friendly, and vivid [ 8 ].

Applications include human-robot communication, where machines react to people based on the emotions they have been programmed to recognise [ 9 ], implementation in call centres to identify the caller’s emotional state in emergencies, determining the degree of a customer’s satisfaction, medical analysis, and education. A conversational chatbot is another suggestion for an emotion recognition application, where real-time SER applications can improve dialogue [ 10 ]. A real-time SER should determine the best compromise between little computer power, quick processing times, and excellent accuracy.

But one of SER’s most significant yet elusive tasks has been identifying the “best” or most distinctive acoustic qualities that describe certain emotions. Despite thorough investigation, the pace of improvement was modest, and there were some discrepancies between studies. Due to these factors, research has shifted toward techniques that do away with or drastically minimise the requirement for prior knowledge of “optimal features” in favour of the autonomous feature-generating processes provided by neural networks [ 11 ]. Both passes employ cutting-edge classifiers, notably convolutional neural networks (CNN) and DNN [ 12 , 13 , 14 ].

Additionally, emotion identification may distinguish between feelings conveyed in only one language or across several languages. However, multilingual emotion recognition is still a new research topic, although many papers on monolingual emotion recognition have been published [ 15 , 16 ]. Therefore, using English, German, and Arabic corpora, extensive experiments and analyses of multilingual emotion recognition based on speech are given in the current study.

The contributions of the study are as follows:

• In this paper, two deep learning models for the SER are proposed: a 1D CNN with LSTM attention and a 2D CNN with multiple layers employing modified kernels and a pooling strategy to detect the sensitive cues-based input extracted features, which tend to be more discriminative and dependable in speech emotion recognition.
• The models above were constructed using varied datasets from multiple languages to make the models more generalisable across language boundaries in analysing emotions based on the vibrational patterns in speech.
• The performance of the proposed 1D CNN with the LSTM attention model is superior to that of the prior attempts on the various speech emotion datasets, suggesting that the proposed SER scheme will contribute to HCI.

The paper is organized as follows: the introduction is in Section 1 , followed by the literature review in Section 2 , then the dataset details, pre-processing, feature extraction, and methodology in Section 3 , followed by the results in Section 4 and discussion in Section 5 , and the conclusions is in Section 6 , followed by the references.

2. Literature Review

Numerous studies have been done on extracting emotions from aural information. The SER system had two essential processes in standard Machine Learning techniques: manual feature extraction and emotion classification. This section discusses existing techniques that leverage various real-time speech emotion recognition datasets and feature extraction techniques available in the literature. Some of the existing models for real-time speech emotion recognition are also discussed in this section.

A flexible emotion recognition system built on the analysis of visual and aural inputs was proposed by [ 17 ] in 2017. Mel Frequency Cepstral Coefficients (MFCC) and Filter Bank Energies (FBEs) were two features used in his study’s feature extraction stage to lower the dimension of previously derived features. The trials used the SAVEE dataset and had a 65.28 percent accuracy rate.

In their suggested method [ 18 ], also used the spectral characteristics, or the 13 MFCC, to categorise the seven emotions with a 70% accuracy rate using the Logistic Model Tree (LMT) algorithm. Results from experiments using the Ryerson Audio-Visual Database of Emotional Speech and Song and the Berlin Database of Emotional Speech (EmoDB) (RAVDESS).

By integrating three models or experts, each focused on different feature extraction and classification strategy [ 19 ], achieved ensemble learning. The study used the IEMOCAP corpus, and a confidence calculation approach was suggested to overcome the IEMOCAP corpus’s data imbalance issue. The study found the key areas of crucial local characteristics work in conjunction with the attention mechanism to exploit each expert’s job from many aspects fully. Seventy-five percent accuracy was achieved [ 20 ].

The authors in [ 21 ] developed a new, lightweight SER model with a low computing overhead and good identification accuracy. The proposed methodology uses a straightforward rectangular filter with a modified pooling strategy that improves SER discriminative performance, as well as a Convolutional Neural Network (CNN) method to learn the deep frequency features. The proposed CNN model was trained using frequency features extracted from the voice data, and its ability to predict emotions was then assessed. The benchmark speech datasets for the proposed SER model were the interactive emotional dyadic motion capture (IEMOCAP) and the Berlin emotional speech database (EMO-DB). The evaluation results were 77.01 and 92.02 percent recognition, respectively.

A novel approach for SER based on the Bidirectional Long Short-Term Memory with Attention (BLSTMwA) model and Deep Convolutional Neural Network (DCNN) was developed by [ 8 ]. (DCNN-BLSTMwA). The speech samples are initially preprocessed using data improvement and dataset balancing. Second, as input for the DCNN, three-channel log Mel-spectrograms (static, delta, and delta-delta) are extracted. The segment-level features are then produced using the DCNN model that has already been trained on the ImageNet dataset. The unweighted average recall (UAR) for experiments using the EMO-DB and IEMOCAP databases was 87.86 and 68.50 percent, respectively [ 22 , 23 , 24 ].

In this work [ 25 ] used recurrent neural network (RNN) designs in their research. Their suggested model extracts relationships from 3D spectrograms across time steps and frequencies by combining parallel convolutional layers (PCN) with a squeeze-and-excitation network (SEnet), also known as PCNSE. Additionally, they used the Interactive Emotional Dyadic Motion Capture (IEMOCAP) and FAU-Aibo Emotion Corpus to demonstrate the viability of the suggested approach (FAU-AEC). On the IEMOCAP dataset, they successfully attained a weighted accuracy (WA) of 73.1 percent, an unweighted accuracy (UA) of 66.3 percent, and a UA of 41.1 percent on the FAU-AEC dataset [ 26 , 27 , 28 ].

Deep Convolutional Recurrent Neural Network was used by [ 29 ] to create an ensemble classifier for speech emotion recognition (SER). This paper introduces a novel method for SER tasks inspired by current work on speech emotion detection. They obtained 3-D log Mel-spectrograms of utterance-level log Mel-spectrograms along with their first and second derivatives (Static, Delta, and Delta-delta). They use deep convolutional neural networks to extract the deep features from 3-D log Mel-spectrograms and deep convolutional neural networks [ 26 ]. An utterance-level emotion is then produced by applying a bi-directional-gated recurrent unit network to express long-term temporal dependency among all features. An ensemble classifier employing Softmax and a Support Vector Machine classifier is used to increase the overall recognition rate [ 27 ]. On the RAVDESS (Eight emotional states) and Odia (Seven emotional states) datasets, the suggested framework is trained and tested. The experiment’s outcomes show that an ensemble classifier outperforms a single classifier in terms of performance. The degrees of accuracy attained are 77.54 percent and 85.31 percent [ 30 , 31 ].

A pre-trained audio-visual Transformer for understanding human behaviour was introduced by [ 32 ]. It was trained on more than 500k utterances from over 4000 celebrities in the VoxCeleb2 dataset. The model’s application in emotion recognition tries to capture and extract relevant information from the interactions between human facial and auditory activities. Two datasets, CREMAD-D (emotion classification) and MSP-IMPROV were used to test the model (continuous emotion regression). According to experimental findings, fine-tuning the pre-trained model increases the consistency correlation coefficients (CCC) in continuous emotion detection by 0.03–0.09 and the accuracy of emotion categorisation by 5–7 percent compared to the same model generated from scratch [ 33 , 34 , 35 ].

We recognize a pattern in the adoption of deep convolutional models that can teach from spectrogram descriptions of speech, per the literature study. There are numerous databases accessible, therefore choosing which databases to use for better training and validation is a difficult process. Although little research has been done on it, the attention mechanism can enhance the performance of SER systems. As a result, we suggested two models in this paper: the 1D CNN with LSTM attention model and the 2D CNN model. The results demonstrate that the proposed models outperformed the existing models in the literature. The brief description of the proposed model is present in the subsequent section.

3. Materials and Methods

This work aims to classify emotions based on the voice signal. The proposed methodology is illustrated in Figure 1 . Based on the findings of individual studies. One cannot definitively state which classifier is superior for emotion recognition. The quality of the data has a direct bearing on the performance of the classifier. This is because the accuracy shifts depending on the characteristics of the data, such as the quantity, and density distribution of each class (emotions), and language as well [ 36 ]. In addition, the model can be trained using the features derived from the audio waves rather than feeding raw audio into a classifier. Since the features are more particular to the issue at hand, the model can be executed more effectively using the features that have been retrieved.

Proposed methodology.

As shown in Figure 1 , the first stage involved the extraction of features from the available labelled datasets, and the second stage involved the classification of the features that were extracted. ZCR, RMSE, and the renowned MFC Coefficients were retrieved as features. Then, two proposed models, 1D CNN combined with LSTM and attention and a proprietary 2D CNN architecture, were used for classification. After that, the evaluation of the performance of the proposed models is presented.

3.1. Datasets

This section briefly describes the datasets such as Arabic Natural Audio Dataset (ANAD) dataset, Basic Arabic Vocal Emotions Dataset (BAVED), The Surrey Audio-Visual Expressed Emotion (SAVEE) database, and The Berlin emotional speech database (EMO-DB).

3.1.1. Arabic Natural Audio Dataset

The (ANAD) [ 37 ] dataset is comprised of three distinct feelings, namely, angry (A), surprised (S), and happy (H). The audio recordings that correlate to these feelings were collected from eight videos of live calls between an anchor and a human located outside the studio. Additionally, the audio files were taken from online discussion programs in Arabic. Eighteen manual labourers contributed to the creation of the ground truth for the videos that were collected. First, they assigned emotions such as anger, surprise, and happiness to each film. The final label is determined by taking the average of the ratings given by all eighteen of the labellers for each video. After that, each film is cut into sections titled “callers” and “receivers”. Next, the areas with laughter, noise, and silence were eliminated. After that, each chunk was automatically broken down into speech units that lasted one second. Figure 2 presents the results of the quantitative analysis performed on the corpus. Figure 2 a demonstrates the distribution of emotions in the ANAD dataset. This figure clearly indicates the count of emotions in three distinct feelings, namely, angry (A), surprised (S), and happy (H).

Distribution of emotions in the ( a ) ANAD, ( b ) BAVED, ( c ) SAVEE, and ( d ) EMO-DB datasets.

3.1.2. Basic Arabic Vocal Emotions Dataset

Basic Arabic Vocal Emotions Dataset (BAVED) [ 38 ] is an audio/wave dataset including Arabic words spelled with varying levels of conveyed emotions. The dataset consisted of the recorded forms of seven Arabic words (0—like, 1—unlike, 2—this, 3—file, 4—good, 5—neutral, and 6—bad) across three emotional degrees. Level 0 is when the speaker expresses a low level of emotion, comparable to feeling exhausted or depressed. Figure 2 b demonstrates the distribution of emotions in the BAVED dataset. Level 1 is the average level, where the speaker expresses neutral feelings; level 2 is when the speaker expresses strong positive or negative emotions (happy, joy, grief, wrath, etc.). The collection consists of 1935 recordings made by 61 speakers (45 males and 16 females).

3.1.3. Surrey Audio-Visual Expressed Emotion Database

The Surrey Audio-Visual Expressed Emotion (SAVEE) database [ 39 ] has been recorded as a prerequisite for creating an automatic emotion identification system. Figure 2 c demonstrates the distribution of emotions in the SAVEE dataset. The collection contains recordings of four male actors expressing seven distinct emotions: sadness, neutral, frustration, happiness, disgust, and anger. The dataset provided 480 British English utterances in total. The sentences were selected from the standard TIMIT corpus and balanced phonetically for each emotion. The data were recorded, analysed, and labelled using high-quality audio-visual equipment at a lab for visual media.

3.1.4. Berlin Database of Emotional Speech

The Berlin emotional speech database, also known as EMO-DB [ 9 ], is a public database that includes information on seven different emotional states. These states are anger, boredom, disgust, fear, happiness, neutral, and sadness. Verbal contents originate from 10 German (5 males and 5 females) pre-defined neutral utterances. It was decided to have ten professional actors read each utterance in each of the seven emotional states. Figure 2 d demonstrates the distribution of emotions in the EMO-DB dataset which shows the count of emotions in the seven distinct types of feelings. The EMO-DB includes around 535 phrases representing each of the seven emotions. The sound files were captured at a sample rate of 16 kHz, a resolution of 16 bits, and a single channel. The length of time for each audio file is, on average, three seconds.

3.2. Feature Extraction

In the feature extraction process, the system extracts as much information as possible from each piece of audio data. For example, the current work extracts the three most relevant features ZCR, RMSE, and MFCC.

3.2.1. Zero Crossing Rate (ZCR)

The zero-crossing rate indicates the frequency at which the signal crosses the zero-amplitude level. Equation (1) provides the calculation of ZCR

where s ( t ) = 1 if the signal has a positive amplitude at t , otherwise 0.

3.2.2. Root Mean Square Error (RMSE)

It is the measure of the energy content in the signal. It is the measure of the energy content in the signal (Equation (2))

3.2.3. Mel Frequency Cepstral Coefficients

Studies in the field of psychophysics have demonstrated that the way humans perceive the sound frequency contents of speech signals does not follow a linear scale. Therefore, a subjective pitch is assessed on a scale referred to as the ‘Mel’ scale. This scale is used for tones with an actual frequency, f , measured in hertz. The conversion of the actual frequency f to mel scale is given in Equation (3).

Mel frequency cepstral coefficients, often known as MFCC, are the individual coefficients that, when added up, form a MFC. They are a form of the cepstral portrayal of the audio sample, where they originated (a nonlinear “spectrum-of-a spectrum”). The typical method for deriving MFCCs is illustrated in Figure 3 . Following the pre-processing stage, the speech frame will go through a hamming window, and then, a rapid Fourier transformation will be used to determine the energy distribution. To get rid of the influence that harmonics have, a Mel filter bank is utilised. The discrete cosine transformation is the last step in the process. In a basic MFCC, the first difference parameters, the second difference parameters, and energy, respectively, make up an N-dimensional MFCC feature.

The MFCC production process.

3.3. Model Development

The methods of classification that were employed are discussed in the following subsections. To improve SER, the 1D CNN with LSTM and attention layers were implemented. In addition to that, a 2D CNN is also demonstrated here. The models were trained using the ZCR, RMSE, and MFCC features retrieved from the data.

3.3.1. One-Dimensional Convolution Neural Network with Long Short-Term Memory and Attention

As shown in Figure 4 , the suggested model consists of five blocks of convolution operations and two completely connected layers. The input to the convolution was retrieved features from the unprocessed audio files that were scaled to fit into 1D convolutional layers. The amount of input varies depending on the utilised dataset. In addition, the weights of the convolution layer must be taught, whereas the pooling layers employ a fixed function to translate the activation. The Rectified Linear Unit (ReLU) is utilised to offer non-linearity to the entire network without affecting the receptive fields of the convolutional layer. Loops improve the effectiveness of the convolution layer. In addition, the model output is produced using a training dataset that includes the loss function, and the learning parameters (kernels and weights) are updated using backpropagation with the loss. Finally, the result is pooled, essentially a nonlinear spatial down-sampling procedure. Pooling reduces the representation’s spatial size, which helps decrease parameters and calculations, preventing overfitting.

The 1D CNN with LSTM attention.

In the second half, CNN’s output is sent into LSTM, determining the more profound temporal link between features. An additional attention layer was a way of acquiring additional information pertinent to each class. Lastly, the pooled feature map is remapped using two layers that are fully connected. Finally, the Softmax layer provided the likelihood of each class’s prediction.

3.3.2. Two Dimensional Convolution Neural Network (CNN)

The structure of the 2D CNN was similar to the common CNNs for the image classification tasks, with the convolution and pooling layers alternatively appearing. However, the number of the convolution and the pooling layers were less compared to the 1D CNN. This is because the primary audio signals were 1D, and the extracted features were 1D, but in the 2D CNN presented in Figure 5 , the convolution kernel, feature map, and other network structures are 2D. Therefore, to process a 1D signal with 2D CNNs, the 1D signal is usually mapped to a 2D space. Then, these 2D features are input into the conventional 2D CNNs for further processing. Finally, an additional dropout layer is added for better training and to avoid overfitting the model.

Two-Dimensional CNN.

3.4. Performance Evaluation

The most common measures that are used to evaluate model performance are presented in this section. Accuracy alone will not be enough; additional metrics such as precision, recall, and the F1-score evaluation criteria will be necessary. The F1- measure is the harmonic mean of the precision, as described by definition [ 40 ].

The experiments conducted to validate the effectiveness of our suggested 1D CNN with the LSTM attention model are shown in this section. To avoid making observations based solely on a corpus examination, four different well-known databases were selected to demonstrate the effectiveness of the suggested approach. An ablation study was first conducted to clarify the advantages of adding LSTM and an attention mechanism to the 1D CNN architecture. A comparison of the created framework’s effectiveness with the outcomes of the designed 2D CNN architecture on the well-known databases ANAD, BAVED, SAVEE, and EMO-DB further emphasises its efficiency.

From the audio samples of each database, the Zero Crossing Rate (ZCR), Root Mean Square Error (RMSE), and Mel-Frequency Cepstral Coefficients (MFCC) features were extracted. The ZCR, which is measured as the number of zero crossings in the temporal domain during one second, is one of the most affordable and basic characteristics. One of the methods most frequently used to assess the accuracy of forecasts is RMSE, also known as the root mean square deviation. It illustrates the Euclidean distance between measured true values and forecasts. The windowing of the signal, application of the DFT, calculation of the magnitude’s log, warping of the frequencies on a Mel scale, and application of the inverse DCT are the main steps in the MFCC feature extraction approach.

Before feature extraction, the data were also enhanced with noise and pitch and provided for model training. The model per epoch evaluation of the model training reveals that the proposed models raise the degree of accuracy and decrease losses for the training and testing datasets, indicating the model’s importance and efficacy. However, some models were stopped early before reaching epoch 50 as the validation accuracy has not improved much. The suggested CNN model’s visual output is depicted in Figure 6 , while the confusion matric acquired are displayed in Figure 7 followed and Figure 8 for Loss and accuracy plots. It displays the results of training the 1D CNN with LSTM attention and 2D CNN models for the four spoken emotion datasets. This indicates the training and validation accuracy and the loss for the BAVED, ANAD, SAVEE, and EMO-DB datasets. Figure 6 presents the loss and accuracy plots during the training process of the 1D CNN with LSTM attention for the different datasets of real-time speech emotion recognition.

Loss and accuracy plots of the ( a ) ANAD, ( b ) BAVED, ( c ) SAVEE, ( d ) EMO-DB datasets for 1D CNN with the LSTM attention model.

Confusion matrix of 1D CNN with the LSTM attention model for the ( a ) ANAD, ( b ) BAVED, ( c ) SAVEE, and ( d ) EMO-DB datasets.

Loss and accuracy plots for the ( a ) ANAD, ( b ) BAVED, ( c ) SAVEE, and ( d ) EMO-DB datasets for the 2D CNN model.

The suggested model is analysed, and the analysis results are presented in Table 1 , while the confusion matric acquired are displayed in Figure 9 . The AUC-ROC curve, recall, precision, and accuracy of the proposed deep learning models can be measured with the use of a confusion matrix. Our model demonstrates accuracy, precision, and recall, as well as the F1-score, which reflects the model’s resilience straightforwardly and concisely. In addition, the performance of the 1D CNN model with LSTM attention layers is much better than that of the 2D CNN model.

Confusion matrix of 2D CNN for the ( a ) ANAD, ( b ) BAVED, ( c ) SAVEE, and ( d ) EMO-DB datasets.

Performance evaluation metrics.

Figure 8 presents the loss and accuracy plots during the training process of the 2D CNN for the different datasets of real-time speech emotion recognition.

The confusion matrix in Figure 7 and Figure 9 and Table 2 , Table 3 , Table 4 and Table 5 clearly explains the model performance in detecting individual emotions on the test dataset.

Individual class performance evaluation metrics—ANAD.

Individual class performance evaluation metrics—BAVED.

Individual class performance evaluation metrics—SAVEE.

Individual class performance evaluation metrics—EMO-DB.

The 1D CNN with the LSTM attention model achieved the highest level of performance when applied to the ANAD dataset. It was clear from Figure 7 a and Table 2 that the best individual performance was achieved for the feeling “Angry” also using the 2D CNN model ( Figure 9 a; Table 2 ), but the performance of the model 1D CNN with LSTM was quite acceptable on the “Surprised” emotion. In contrast, the performance of the 2D CNN was much worse for the “Surprised” emotion state, which greatly damaged the model’s overall accuracy.

Compared to the ANAD dataset, the performance of the BAVED dataset was significantly lower, even though it was also an Arabic dataset. The two distinct models each had a distinct impact on the performance of their respective particular classes. The “Neutral” emotion class achieved the highest performance when the 1D CNN model was evaluated. However, the performance of the 2D CNN is superior for the “Low” emotion class ( Table 3 ; Figure 7 b and Figure 9 b).

For the SAVEE datasets ( Table 4 ; Figure 7 c and Figure 9 c), the performance of predicting “Happy”, “Surprised”, and “Neutral” emotions was highest with a 1D CNN model. In contrast, the performance of predicting these emotions with a 2D CNN model was very much lower. The performance was only improved for the emotion “Neutral” option, and even then, it was only 77% recall. Compared to the inferior emotion (“Fear”, with a recall of 95 percent) that could be predicted using 1D CNN, this prediction was much less accurate.

The trend seen in SAVEE can also be seen in the German dataset -EMO-DB. The performance of the 1D CNN with LSTM attention demonstrated a significant and noticeable difference. The emotions that performed the best with 1D CNN were “Disgust” and “Anger”. “Anger” still predominates on 2D CNN, but “Disgust” is relatively low. “Sad” performed better ( Table 5 ; Figure 7 d and Figure 9 d).

5. Discussion

Speech Emotion Recognition is one of the contributing factors to human–computer interaction. The human brain processes the multimodalities to extract the spatial and temporal semantic information that is contextually meaningful to perceive and understand an individual’s emotional state. However, for machines, even though human speech contains a wealth of emotional content, it is challenging to predict the emotions or the speaker’s intention hidden in their voice [ 41 ].

5.1. Dataset Variability

For the SER challenge, several of the earlier efforts only included a single language dataset [ 42 ] and nevertheless managed to obtain excellent performance on that dataset. Despite its outstanding performance, the model was constructed using only one language, limiting its ability to comprehend various feelings. Due to this, the evaluation of the potential for generalisation, and consequently the real-world impact of the different techniques, is effectively constrained [ 43 ]. Robust embeddings for speech emotion identification should perform well across various languages to act as a paralinguistic cue [ 44 ]. However, human speech is so diverse and dynamic that no model can be reserved to be used forever [ 45 ].

Additionally, the diversity of languages causes an imbalance of available datasets for emotion recognition for minority languages compared to well-established majority languages such as English. This is particularly true for languages that are spoken by a smaller population. Despite this, it is necessary to develop a generalised model for multilingual emotional data for us to use the currently available datasets. The proposed model was validated by testing it on four datasets spanning three distinct languages, each with a different dataset size and a different category of emotions. Even though the performance was not very good on some datasets, the model tried to achieve a generalisation across different sets of emotions expressed in different languages.

5.2. Feature Extraction

The current work was designed similarly to the traditional ML pipeline, with the manually extracted features contributing to the model classification. ZCR, RMSE, and the MFCCs were the features extracted. Although no Feature Selection has been performed, MFCCs have been selected because they are the most common representation in traditional audio signal processing, but the most recent works used spectrogram images as the input for developing deep learning models [ 46 ]. Some of them used raw audio waveforms also [ 47 ]. Raw waveforms and spectrograms avoid hand-designed features, which should allow better to exploit the improved modelling capability of deep learning models, learning representations optimised for a task. However, this incurs higher computational costs and data requirements, and benefits may be hard to realise in practice. Handcrafted features, even though incorporating huge manual tasks, understanding the features contributing to the classification task would be more efficient than manual feature extraction, especially for complex audio recognition tasks such as emotion recognition. The proposed work outperformed the work on image spectrograms, with an accuracy of 86.92% for EMO-DB and 75.00% for SAVEE datasets [ 46 ] and 95.10% for EMO-DB and 82.10% for SAVEE [ 48 ] ( Table 6 ).

Performance comparison of the works in the EMO-DB dataset.

5.3. Classification

In this study, CNNs are used to construct the particular model with additional LSTM with attention. For example, the speech signal is a time-varying signal which needs particular processing to reflect time-fluctuating features [ 49 ]. Therefore, the LSTM layer is introduced to extract long-term contextual relationships. The results revealed that the 1D CNN model produced with LSTM had outperformed the model developed with 2D CNN architecture for all the datasets included in the study ( Table 1 ). [ 50 ] followed the same pipeline as our study, where they retrieved manual features from the audio, such as MFCCs. They even included the feature selection method, but the Linear SVM classifier was used, but with a comparatively lightweight model, they obtained an accuracy of 96.02%, which is much closer to our findings. However, the proposed model was inferior to the model produced by [ 51 ] using the BAVED database. In another work [ 52 ] this technique is also applied. They used wav2vec2.0 and HuBERT as the feature extractors and the classifier head as the Multi-layer Perception Classifier coupled to a Bi-LSTM Layer with 50 hidden units. The performance is as shown in Table 7 , Table 8 and Table 9 .

Performance comparison of the works in the SAVEE dataset.

Performance comparison of the works in the ANAD dataset.

Performance comparison of the works in the BAVED dataset.

The current effort sought to construct an SER capable of generalising across the language boundaries in speech emotion detection. The performance of the model was satisfactory. However, there is still an opportunity for further progress in some languages. In the future study, more extensive datasets from various disciplines will be focused on to get a better SER model for a more productive human–computer interaction. The field of human–computer interaction, especially voice-based interaction, is developing and changing virtually every day. The current work aims to construct artificially intelligent systems based on deep learning for recognising human emotions based on many modalities. In this paper, a unique 1D CNN architecture with LSTM and attention layers was created, as well as a 2D CNN, to recognise emotions expressed in Arabic, English, and German utterances. Before starting the model training process, the MFCC, ZCR, and RMSE features were retrieved. The learning models were implemented, and then, the outcomes of these models were exhibited using the audio dataset available in three languages. The proposed 1D CNN design with LSTM and attention layers recognised emotions with more precision than the 2D CNN architecture. The model’s accuracy was achieved at 96.72%, 97.13%, 96.72%, and 88.39% for the EMO-DB, SAVEE, ANAD, and BAVED datasets.

5.4. Limitations

The current work is performing well in terms of results and accuracy compared to other works, but it is observed that it is a little complex. The performance complexity evaluation is a bit heavy, and it can be resolved. Therefore, in the upcoming future, this can be taken into consideration for the smooth performance of the system.

6. Conclusions

The field of human–computer interaction, especially voice-based interaction, is developing and changing virtually every day. The current work aims to construct artificially intelligent systems based on deep learning for recognising human emotions based on many modalities. In this paper, a unique 1D CNN architecture with LSTM and attention layers was created, as well as a 2D CNN, to recognise emotions expressed in Arabic, English, and German utterances. Before starting the model training process, the MFCC, ZCR, and RMSE features were retrieved. The learning models were implemented, and then, the outcomes of these models were exhibited using the audio dataset available in three languages. The results revealed that the 1D CNN model produced with LSTM outperformed the model developed with 2D CNN architecture for all the datasets included in the study. The performance of the model was satisfactory; additionally, the performance of the 2D CNN was superior for the “Low” emotion class. The proposed model outperformed the work on image spectrograms, with an accuracy of 86.92% for EMO-DB, 75.00% for SAVEE [ 46 ], 95.10% for EMO-DB, and 82.10% for SAVEE. The proposed 1D CNN design with LSTM and attention layers recognised emotions with more precision than the 2D CNN architecture. The model’s accuracy was achieved at 96.72%, 97.13%, 96.72%, and 88.39% for the EMO-DB, SAVEE, ANAD, and BAVED datasets.

Acknowledgments

The author would like to thank Al Faisal University, College of Engineering for all the support.

Funding Statement

The author received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The author declares no conflict of interest.

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Paralysis can rob people of their ability to speak. Now researchers hope to give it back

When Jaimie Henderson was 5 years old, his father was in a devastating car crash. The accident left his father barely able to move or speak. Henderson remembers laughing at his dad's jokes, though he never could understand the punchlines. "I grew up wishing I could know him and communicate with him."

That early experience drove his professional interest in helping people communicate.

Now, Henderson's an author on one of two papers published Wednesday showing substantial advances toward enabling speech in people injured by stroke, accident or disease.

Although still very early in development, these so-called brain-computer interfaces are five times better than previous generations of the technology at "reading" brainwaves and translating them into synthesized speech. The successes suggest it will someday be possible to restore nearly normal communication ability to people like Henderson's late father.

"Without movement, communication is impossible," Henderson said, referencing the trial's participant who has amyotrophic lateral sclerosis, or ALS , which robs people of their ability to move. "We hope to one day tell people who are diagnosed with this terrible disease that they will never lose the ability to communicate."

Both the technologies, developed at Stanford and nearby at the University of California, San Francisco , enabled a volunteer to generate 60 to 80 words per minute. That's less than half the pace of normal speech, which typically ranges from 150 to 200 words per minute, but substantially faster than previous brain-computer interfaces. The new technologies can also interpret and produce a much broader vocabulary of words, rather than simply choosing from a short list.

At Stanford, researchers chose to decode signals from individual brain cells. The resolution will improve as the technology gets better at allowing recording from more cells, Henderson said.

"We're sort of at the era of broadcast TV, the old days right now," he said in a Tuesday news conference with reporters. "We need to increase the resolution to HD and then on to 4K so that we can continue to sharpen the picture and improve the accuracy."

The two studies "represent a turning point" in the development of brain-computer interfaces aimed at helping paralyzed people communicate, according to an analysis published in the journal Nature along with the papers .

"The two BCIs represent a great advance in neuroscientific and neuroengineering research, and show great promise in boosting the quality of life of individuals who have lost their voice as a result of paralysing neurological injuries and diseases," wrote Dutch neurologist Nick Ramsey and Johns Hopkins University School of Medicine neurologist Nathan Crone.

Paralyzed patients walking in minutes: New electrode device a step forward in spinal injury care

Two different approaches to communication, both work

At UCSF, researchers chose to implant 253 high-density electrodes across the surface of a brain area involved in speech.

The fact that the different approaches both seem to work is encouraging, the two teams said Tuesday.

It's too early to say whether either will ultimately prove superior or if different approaches will be better for different types of speech problems. Both teams implanted their devices into the brains of just one volunteer each, so it's not yet clear how challenging it will be to get the technology to work in others.

The UCSF team also personalized the synthesized voice and created an avatar that can recreate the facial expressions of the participant, to more clearly reeplicate natural conversation. Many brain injuries, like ALS and stroke also paralyze the muscles of the face, leaving the person unable to smile, look surprised, or offer concern.

Ann, the participant in the USCF trial, had a brain stem stroke 17 years ago and has been participating in the research since last year. Researchers identified her only by her first name to protect her privacy.

The electrodes intercepted brain signals that, if not for Ann's stroke, would have gone to muscles in her, tongue, jaw and larynx, as well as her face, according to UCSF. A cable, plugged into a port fixed to her head, connected the electrodes to a bank of computers.

For weeks, she and the team trained the system’s artificial intelligence algorithms to recognize her distinctive brain signals by repeating phrases over and over again.

Instead of recognizing whole words, the AI decodes words from phonemes, according to UCSF. “Hello,” for example, contains four phonemes: “HH,” “AH,” “L” and “OW."

Researchers used video from Ann's wedding to create a computer-generated voice that sounds much like her own did and to create an avatar that can make facial expressions similar to the ones she made before her stroke.

Advances in machine learning have made such technologies possible, said Sean Metzger, a bioengineering graduate student who helped lead the research. " Overall, I think this work represents accurate and naturalistic decoding of three different speech modalities, text, synthesis and an avatar to hopefully restore fuller communication experience for our participant," he told reporters.

The healing power of a good beat: Neurologic music therapy helps kids with brain injuries

Stanford approach: Tiny sensors on the brain

The Stanford trial relied on volunteer Pat Bennett, now 68, a former human resources director, who was diagnosed with ALS in 2012.

“When you think of ALS, you think of arm and leg impact,” Bennett wrote in an interview with Stanford staff conducted by email and provided to the media. “But in a group of ALS patients, it begins with speech difficulties. I am unable to speak.”

On March 29, 2022, neurosurgeons at Stanford placed two tiny sensors each on the surface of two regions of Bennett's brain involved in speech production. About a month later, she and a team of Stanford scientists began twice-weekly, four-hour research sessions to train the software that was interpreting her speech.

She would repeat in her mind sentences chosen randomly from telephone conversations, such as: “It’s only been that way in the last five years.” Another: “I left right in the middle of it.”

As she recited these sentences, her brain activity was translated by a decoder into a stream of "sounds" and then assembled into words. Bennett repeated 260 to 480 sentences per training session. Initially, she was restricted to a 50-word vocabulary, but then allowed to choose from 125,000 words, essentially, all she would ever need.

After four months, she was able to generate 62 words per minute on a computer screen merely by thinking them.

“For those who are nonverbal, this means they can stay connected to the bigger world, perhaps continue to work, maintain friends and family relationships,” she wrote.

The technology made a lot of mistakes. About 1 out of every 4 words was interpreted incorrectly even after this training.

Frank Willett, the research scientist who helped lead the Stanford work, said he hopes to improve accuracy in the next few years, so that only 1 out of 10 words will be wrong.

Edward Chang, the senior researcher on the UCSF paper, said he hopes his team's work will "really allow people to interact with digital spaces in new ways," communicating beyond simply articulating words.

All four researchers said restoring communication abilities to Ann and Bennett during the trial was a highlight in their professional careers.

"It was quite emotional for all of us to see this work," said Chang, a member of the UCSF Weill Institute for Neuroscience.

"I felt like I'd come full circle from wishing I could communicate with my dad as a kid to seeing this actually work," Henderson added. "It's indescribable."

Contact Karen Weintraub at [email protected].

Health and patient safety coverage at USA TODAY is made possible in part by a grant from the Masimo Foundation for Ethics, Innovation and Competition in Healthcare. The Masimo Foundation does not provide editorial input .

Best text-to-speech software of 2024

Boosting accessibility and productivity

• Best overall
• Best realism
• Best for developers
• Best for podcasting
• How we test

The best text-to-speech software makes it simple and easy to convert text to voice for accessibility or for productivity applications.

1. Best overall 2. Best realism 3. Best for developers 4. Best for podcasting 5. Best for developers 6. FAQs 7. How we test

Finding the best text-to-speech software is key for anyone looking to transform written text into spoken words, whether for accessibility purposes, productivity enhancement, or creative applications like voice-overs in videos. 

Text-to-speech (TTS) technology relies on sophisticated algorithms to model natural language to bring written words to life, making it easier to catch typos or nuances in written content when it's read aloud. So, unlike the best speech-to-text apps and best dictation software , which focus on converting spoken words into text, TTS software specializes in the reverse process: turning text documents into audio. This technology is not only efficient but also comes with a variety of tools and features. For those creating content for platforms like YouTube , the ability to download audio files is a particularly valuable feature of the best text-to-speech software.

While some standard office programs like Microsoft Word and Google Docs offer basic TTS tools, they often lack the comprehensive functionalities found in dedicated TTS software. These basic tools may provide decent accuracy and basic options like different accents and languages, but they fall short in delivering the full spectrum of capabilities available in specialized TTS software.

To help you find the best text-to-speech software for your specific needs, TechRadar Pro has rigorously tested various software options, evaluating them based on user experience, performance, output quality, and pricing. This includes examining the best free text-to-speech software as well, since many free options are perfect for most users. We've brought together our picks below to help you choose the most suitable tool for your specific needs, whether for personal use, professional projects, or accessibility requirements.

The best text-to-speech software of 2024 in full:

Why you can trust TechRadar We spend hours testing every product or service we review, so you can be sure you’re buying the best. Find out more about how we test.

Below you'll find full write-ups for each of the entries on our best text-to-speech software list. We've tested each one extensively, so you can be sure that our recommendations can be trusted.

The best text-to-speech software overall

1. NaturalReader

Our expert review:

Reasons to buy

Reasons to avoid.

If you’re looking for a cloud-based speech synthesis application, you should definitely check out NaturalReader. Aimed more at personal use, the solution allows you to convert written text such as Word and PDF documents, ebooks and web pages into human-like speech.  

Because the software is underpinned by cloud technology, you’re able to access it from wherever you go via a smartphone, tablet or computer. And just like Capti Voice, you can upload documents from cloud storage lockers such as Google Drive, Dropbox and OneDrive.  

Currently, you can access 56 natural-sounding voices in nine different languages, including American English, British English, French, Spanish, German, Swedish, Italian, Portuguese and Dutch. The software supports PDF, TXT, DOC(X), ODT, PNG, JPG, plus non-DRM EPUB files and much more, along with MP3 audio streams. 

There are three different products: online, software, and commercial. Both the online and software products have a free tier.

Read our full NaturalReader review .

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The best text-to-speech software for realistic voices

Specializing in voice synthesis technology, Murf uses AI to generate realistic voiceovers for a range of uses, from e-learning to corporate presentations. 

Murf comes with a comprehensive suite of AI tools that are easy to use and straightforward to locate and access. There's even a Voice Changer feature that allows you to record something before it is transformed into an AI-generated voice- perfect if you don't think you have the right tone or accent for a piece of audio content but would rather not enlist the help of a voice actor. Other features include Voice Editing, Time Syncing, and a Grammar Assistant.

The solution comes with three pricing plans to choose from: Basic, Pro and Enterprise. The latter of these options may be pricey but some with added collaboration and account management features that larger companies may need access to. The Basic plan starts at around $19 / £17 / AU$28 per month but if you set up a yearly plan that will drop to around $13 / £12 / AU$20 per month. You can also try the service out for free for up to 10 minutes, without downloads.

The best text-to-speech software for developers

3. Amazon Polly

Alexa isn’t the only artificial intelligence tool created by tech giant Amazon as it also offers an intelligent text-to-speech system called Amazon Polly. Employing advanced deep learning techniques, the software turns text into lifelike speech. Developers can use the software to create speech-enabled products and apps. 

It sports an API that lets you easily integrate speech synthesis capabilities into ebooks, articles and other media. What’s great is that Polly is so easy to use. To get text converted into speech, you just have to send it through the API, and it’ll send an audio stream straight back to your application. 

You can also store audio streams as MP3, Vorbis and PCM file formats, and there’s support for a range of international languages and dialects. These include British English, American English, Australian English, French, German, Italian, Spanish, Dutch, Danish and Russian. 

Polly is available as an API on its own, as well as a feature of the AWS Management Console and command-line interface. In terms of pricing, you’re charged based on the number of text characters you convert into speech. This is charged at approximately $16 per1 million characters , but there is a free tier for the first year.

The best text-to-speech software for podcasting

In terms of its library of voice options, it's hard to beat Play.ht as one of the best text-to-speech software tools. With almost 600 AI-generated voices available in over 60 languages, it's likely you'll be able to find a voice to suit your needs. 

Although the platform isn't the easiest to use, there is a detailed video tutorial to help users if they encounter any difficulties. All the usual features are available, including Voice Generation and Audio Analytics. 

In terms of pricing, Play.ht comes with four plans: Personal, Professional, Growth, and Business. These range widely in price, but it depends if you need things like commercial rights and affects the number of words you can generate each month. 

The best text-to-speech software for Mac and iOS

5. Voice Dream Reader

There are also plenty of great text-to-speech applications available for mobile devices, and Voice Dream Reader is an excellent example. It can convert documents, web articles and ebooks into natural-sounding speech. 

The app comes with 186 built-in voices across 30 languages, including English, Arabic, Bulgarian, Catalan, Croatian, Czech, Danish, Dutch, Finnish, French, German, Greek, Hebrew, Hungarian, Italian, Japanese and Korean. 

You can get the software to read a list of articles while you drive, work or exercise, and there are auto-scrolling, full-screen and distraction-free modes to help you focus. Voice Dream Reader can be used with cloud solutions like Dropbox, Google Drive, iCloud Drive, Pocket, Instapaper and Evernote. 

The best text-to-speech software: FAQs

What is the best text-to-speech software for youtube.

If you're looking for the best text-to-speech software for YouTube videos or other social media platforms, you need a tool that lets you extract the audio file once your text document has been processed. Thankfully, that's most of them. So, the real trick is to select a TTS app that features a bountiful choice of natural-sounding voices that match the personality of your channel. 

What’s the difference between web TTS services and TTS software?

Web TTS services are hosted on a company or developer website. You’ll only be able to access the service if the service remains available at the whim of a provider or isn’t facing an outage.

TTS software refers to downloadable desktop applications that typically won’t rely on connection to a server, meaning that so long as you preserve the installer, you should be able to use the software long after it stops being provided. 

Do I need a text-to-speech subscription?

Subscriptions are by far the most common pricing model for top text-to-speech software. By offering subscription models for, companies and developers benefit from a more sustainable revenue stream than they do from simply offering a one-time purchase model. Subscription models are also attractive to text-to-speech software providers as they tend to be more effective at defeating piracy.

Free software options are very rarely absolutely free. In some cases, individual voices may be priced and sold individually once the application has been installed or an account has been created on the web service.

How can I incorporate text-to-speech as part of my business tech stack?

Some of the text-to-speech software that we’ve chosen come with business plans, offering features such as additional usage allowances and the ability to have a shared workspace for documents. Other than that, services such as Amazon Polly are available as an API for more direct integration with business workflows.

Small businesses may find consumer-level subscription plans for text-to-speech software to be adequate, but it’s worth mentioning that only business plans usually come with the universal right to use any files or audio created for commercial use.

How to choose the best text-to-speech software

When deciding which text-to-speech software is best for you, it depends on a number of factors and preferences. For example, whether you’re happy to join the ecosystem of big companies like Amazon in exchange for quality assurance, if you prefer realistic voices, and how much budget you’re playing with. It’s worth noting that the paid services we recommend, while reliable, are often subscription services, with software hosted via websites, rather than one-time purchase desktop apps. 

Also, remember that the latest versions of Microsoft Word and Google Docs feature basic text-to-speech as standard, as well as most popular browsers. So, if you have access to that software and all you’re looking for is a quick fix, that may suit your needs well enough. 

How we test the best text-to-speech software

We test for various use cases, including suitability for use with accessibility issues, such as visual impairment, and for multi-tasking. Both of these require easy access and near instantaneous processing. Where possible, we look for integration across the entirety of an operating system , and for fair usage allowances across free and paid subscription models.

At a minimum, we expect an intuitive interface and intuitive software. We like bells and whistles such as realistic voices, but we also appreciate that there is a place for products that simply get the job done. Here, the question that we ask can be as simple as “does this piece of software do what it's expected to do when asked?”

Read more on how we test, rate, and review products on TechRadar .

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John (He/Him) is the Components Editor here at TechRadar and he is also a programmer, gamer, activist, and Brooklyn College alum currently living in Brooklyn, NY. 

Named by the CTA as a CES 2020 Media Trailblazer for his science and technology reporting, John specializes in all areas of computer science, including industry news, hardware reviews, PC gaming, as well as general science writing and the social impact of the tech industry.

You can find him online on Threads @johnloeffler.

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• Speech about Life for Students and Children

Speech about Life

Good morning one and all present here. I am standing before you all to share my thoughts through my speech about life. Life is a continuous ongoing process that has to end someday. Life is all about adoring yourself, creating yourself. A quote for you that life can be only understood backward but it must be lived forwards. Life itself is a golden opportunity to live a meaningful life and support others to do so. It doesn’t matter how many years you live. But it matters how well you live a quality life.

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The fear of death always threatens our lives. Every person has to face death sooner or later, but that doesn’t mean that it should discourage us from living life to the fullest or achieving our goals. A person is wise only when he/she is ready to meet destiny when it comes, but until that time enjoys every bit of it. It is a sense of readiness. It is a journey in everyone’s life wherein we have to cross the bridge of death to be able to wake up to a life eternal.

Get the Huge list of 100+ Speech Topics here

Human life – A very Precious Gift

Human life is truly a very precious gift. Each moment of human life carries us an opportunity, to act to develop and express our virtues. Every moment unlocks the path to us to receive blessings. This is the truth that life gives us both positive and negative situations. What is really important is how we react.

Life is the gift of God in the form of trust that we will make it meaningful in whatever we can. We are all unique individuals. No one is born like you and no one will ever be, so cherish your individuality. Many times, I come across people accusing God of things that they don’t have. They always cursing their lives. But, do they realize that this life itself is precious? If we make it worth living and work hard towards positivity.

Life is a Journey, not a Destination

Life is nothing but a journey with lessons, hardships, heartache and special moments. It will ultimately lead us to our destination, our purpose in life. The road will not always be a plane; in fact, throughout our travels, we will face many challenges.

These challenges will always test our courage, strengths, weaknesses, and faith. Along our way, we may encounter obstacles that will come between the paths and we are destined to take.

In order to be on the right path, we must overcome these obstacles. Sometimes these obstacles are really blessings in disguise, only we don’t understand that at the time. The secret of life is best known to those who are not attached to anything deeply so much.

Therefore, they remain out of touch with worries and shifting fortunes of their lives. They are the people who do not measure their lives in terms of materialistic possessions, but by measuring their lives in terms of people they cannot live without.

Lastly, I will conclude that we should make life worthwhile. It should be with the love of our family and friends that life can be made beautiful. Life can be more beautiful and purposeful by discharging our duties in our family, at work, society and the world at large.

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16 responses to “Speech on Water for Students and Children”

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Very helpful in my speech

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Very much helpful and its well crafted and expressed. Thumb’s up!!!

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