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Top 10 Best Open Source Speech Recognition Tools for Linux

Speech is a popular and smart method in modern time to make interaction with electronic devices. As we know, there are many open source speech recognition tools available on different platforms. From the beginning of this technology, it has been improved simultaneously in understanding the human voice. This is the reason; it has now engaged a lot of professionals than before. The technical advancement is strong enough to make it more clear to the common people.

Open Source Speech Recognition Tools

Open source voice recognition tool is not much available like the typical software we use in our daily lives in Linux platform. After a long way of research, we found some well-featured applications for you with a short description. Let’s have a look at the points below!

Kaldi is a special kind of speech recognition software, started as a part of a project at John Hopkins University. This toolkit comes with an extensible design and written in C++ programming language. It provides a flexible and comfortable environment to its users with a lot of extensions to enhance the power of Kaldi.

Noteworthy Features of Kaldi

A free and flexible open source voice recognition application, under the Apache license.
Runs on multiple platforms, including GNU/Linux , BSD, and Microsoft Windows.
Provides support to install and configure the application to your system.
Besides the speech recognition system, it also supports deep neural networks and linear transforms.

2. CMUSphinx

CMUS Sphinx comes with a group of featured-enriched systems with several pre-built packages related to speech recognition. It is an open source program , developed at Carnegie Mellon University. You will get this speaker-independent recognition tool in several languages, including French, English, German, Dutch, and more.

cmusphinx- open source voice recognition

Noteworthy Features of CMUSphinx

It is an easy-to-use and fast speech recognition system with a user-friendly interface.
Comes with a flexible design and efficient system, even in low resource platforms.
Provides acoustic model training tools through its Sphinxtrain package.
Helps to perform different types of tasks through its helpful packages, including keyword spotting, pronunciation evaluation, alignment, and more.
It is a cross-platform tool that supports both Windows and Linux systems.

Get CMUSphinx

3. DeepSpeech

DeepSpeech is an open source speech recognition engine to convert your speech to text. It is a free application by Mozilla. To run DeepSearch project to your device, you will need Python 3.r or above. Also, it needs a Git extension file, namely Git Large File Storage. It is used for versioning large files while you run it to your system.

Noteworthy Features of DeepSpeech

DeepSpeech uses TensorFlow framework to make the voice transformation more comfortable.
It supports NVIDIA GPU, which helps to perform quicker inference.
You can use the DeepSearch inference in three different ways; The Python package, Node.JS package, or Command-line client .
Each time you want to run this software to your system, you’ll need to activate the virtual environment by Python command.
It needs a Linux or Mac environment to run this application.

Get DeepSpeech

4. Wav2Letter++

WavLetter++ is a modern and popular speech recognition tool, developed by the Facebook AI Research team. It is another open source program under the BCD license. This superfast voice recognition software was built in C++ and introduced with a lot of features. It provides the facility of language modeling, machine translation, speech synthesis, and more to its users in a flexible environment.

Noteworthy Features of Wav2Letter++

It contains an active community in popular platforms like Facebook and Google group to assist its users worldwide.
WavLetter++ is a fast and flexible toolkit which uses ArrayFire tensor library for the maximum efficiency.
It lets you work with a high-performance framework like wav2letter++, which helps to do a successful research and model tuning.
Also, it provides complete documentation through the tutorial sections.
In the recipes folder, you will get the detailed recipes for WSJ, Timit, and Librispeech.

Get Wav2Letter++

Julius is comparatively an older open source voice recognition software developed by Lee Akinobu. This tool is written in the C programming language by the developers of Kawahara Lab, Kyoto University. It is a high-performance speech recognition application having a large vocabulary. You can use it in both English and Japanese languages. It can be a great choice if you want to use it for academic and research purposes.

Noteworthy Features of Julius

Julius is a highly configurable application that can set different search parameters to tune its performance.
This tool is based on a 2-pass strategy which provides you a real-time and high-quality performance.
It is a cross-platform project that runs on Linux, BSD, Windows, and Android Systems.
Integrated with Julian, a grammar-based recognition parser.
Besides supporting rule-based grammar, it also provides Word graph output, Confidence scoring, GMM-based input rejection, and many more facilities.

Get Julius

Simon comes with a modern and easy-to-use speech recognition software, developed by Peter Grasch. It is another open source program under the GNU General Public License. You are free to use Simon in both Linux and Windows systems. Also, it provides the flexibility to work with any language you want.

Noteworthy Features of Simon

Using its voice-controlled calculator, Simon provides the facility to do various arithmetic operations.
Compatible with Skype and other popular VOIP programs to establish an easy communication system with friends and relatives.
It allows users to watch slide shows and videos, listen to music , and more with a few simple voice commands.
Also, it is an essential tool in reading newspapers and surfing the internet.

Mycroft comes with an easy-to-use open source voice assistant for converting voice to text. It is regarded as one of the most popular Linux speech recognition tools in modern time, written in Python. It allows users to make the best use of this tool in a science project or enterprise software application. Also, it can be used as a practical assistant, that can tell you the time, date, weather, and more like these.

Noteworthy Features of Mycroft

Integrated with the most popular social media and professional platforms, including Facebook, Github , LinkedIn, and more.
You can run this application on different software and hardware platforms. It can be a desktop or a Raspberry Pi .
Besides being a smart voice assistant, it provides the facility of the audio record, machine learning, software library, and more.
It lets users convert the natural language to machine-readable data through Adapt, an intent parser of Mycroft.

Get Mycroft

8. OpenMindSpeech

Open Mind Speech is one of the essential Linux speech recognition tools aims to convert your speech to text for free. It is a part of Open Mind Initiative, runs its operation, especially for developers. This program was introduced with different names like VoiceControl, SpeechInput, and FreeSpeech before getting the present name.

Noteworthy Features of OpenMindSpeech

It uses the Overflow environment in the voice recognition operation to make the complex applications flexible.
Open Mind Speech is mostly compatible with Linux and UNIX-based platforms.
Using the internet, it can collect speech data from e-citizens, who are the contributors of raw data.

Get OpenMindSpeech

9. SpeechControl

Speech Control is a free speech recognition application, suitable for any Ubuntu distro. It comes with a graphical user interface based on Qt. Though it is still in its early development stage, you can use it for your simple project.

speechcontrol-open source voice recognition

Noteworthy Features of SpeechControl

Speech Control is an open source program under the General Public License (GPL).
It aims to work as a virtual assistant that provides repetitive task guidance to execute the process smoothly.
It is mostly suitable for Linux-based platforms.
Also, provides easy-to-understand user documentation with project details.

Get SpeechControl

10. Deepspeech.pytorch

Deepspeech.pytorch is another mentionable open source speech recognition application which is ultimately implementation of DeepSpeech2 for PyTorch. It contains a set of powerful networks based DeepSpeech2 architecture. With many helpful resources, it can be used as one of the essential Linux speech recognition tools for research and project development.

Noteworthy Features of Deepspeech.pytorch

Supports noise augmentation that helps to increase robustness at the time of loading audio.
To send the post request to the server, it provides a basic server script.
Support several datasets for downloading, including TEDLIUM, AN4, Voxforge, and LibriSpeech.
Lets you add noise into the training data through noise injection.
Supports Visdom and Tensorboard for visualizing training on scientific experimentation.

Get Deepspeech.pytorch

Finishing Thoughts

So, we have reached the finishing point on open source speech recognition tools for Linux. Hope, you got comprehensive information regarding this topic. The above-mentioned applications are free, easy-to-use, and ready to be a part of your academic or personal project.

Which one do you prefer most? If you have any other choices, then don’t hesitate to let us know. Please do share this article with your community, if you get it helpful. Till then, have a nice time. Thanks!

I dont understand alot of this github stuff i just need a deb

i just want to talk to my computer

I frequently make live videos (usually streamed by Instagram or Facebook) and I would like to know if there is a software that can automatically transcribe what I say in these videos, like Youtube does automatically for subtitles. Anyone can help? Thanks

I’m searching for a simple speech recognition to create a variable to select audio files to play for a blind person. This lady only wants to listen to a Bible version called The Message Bible. Unfortunately it isn’t available in a manner that doesn’t require the User to respond to visual selections. I envision a simple command line file triggered by a variable created by her voice when she says something like “Goto the book of Psalms, chapter 23. (since Psalms is indexed by Psalm they would be inside folders marked as chapters.

13 Best Free Linux Speech Recognition Tools

Speech is an increasingly popular method of interacting with electronic devices such as computers, phones, tablets, and televisions. Speech is probabilistic, and speech engines are never 100% accurate. But technological advances have meant speech recognition engines offer better accuracy in understanding speech. The better the accuracy, the more likely customers will engage with this method of control. And, according to a study by Stanford University, the University of Washington and Chinese search giant Baidu, smartphone speech is three times quicker than typing a search query into a screen interface.

Witness the rise of intelligent personal assistants, such as Siri for Apple, Cortana for Microsoft, and Mycroft for Linux. The assistants use voice queries and a natural language user interface to attempt to answer questions, make recommendations, and perform actions without the requirement of keyboard input. And the popularity of speech to control devices is testament to dedicated products that have dropped in large quantities such as Amazon Echo. Speech recognition is also used in smart watches, household appliances, and in-car assistants. In-car applications have lots of mileage (excuse the pun). Some of the in-car applications include navigation, asking for weather forecasts, finding out the traffic situation ahead, and controlling elements of the car, such as the sunroof, windows, and music player.

The key challenge for developing speech recognition software, whether it’s used in a computer or another device, is that human speech is extremely complex. The software has to cope with varied speech patterns, and individuals’ accents. And speech is a dynamic process without clearly distinguished parts. Fortunately, technical advancements have meant it’s easier to create speech recognition tools. Powerful tools like machine learning and artificial intelligence, coupled with improved speech algorithms, have altered the way these tools are developed. You don’t need phoneme dictionaries. Instead, speech engines can employ deep learning techniques to cope with the complexities of human speech.

There aren’t that many speech recognition toolkits available, and some of them are proprietary software. Fortunately, there are some very exciting open source speech recognition toolkits available. These toolkits are meant to be the foundation to build a speech recognition engine.

This article highlights the best open source speech recognition software for Linux. The rating chart summarizes our verdict.

Ratings chart for best free and open source speech recognition tools

Let’s explore the 13 free speech recognition tools at hand. For each title we have compiled its own portal page with a full description and an in-depth analysis of its features.

This site uses Akismet to reduce spam. Learn how your comment data is processed .

What is really wrong with the license terms of HTK?

This clause is particularly damning:

2.2 The Licensed Software either in whole or in part can not be distributed or sub-licensed to any third party in any form.

…and nothing else matters…

Sadly my machine doesn’t have sufficient RAM on my graphics card to experiment with DeepSpeech. Any recommendations for a good GPU that works well with DeepSpeech?

Thanks for the comprehensive info regarding the open source tools. From the perspective of a visually impaired person, what I would like to know is which of these would be most suitable (now or in near future) for dictating to get text that could go into documents, e-mail, etc. Is that Simon?

Yes, Simon is very good for what you’re looking for. Most of the other open source speech recognition tools are not really aimed at a desktop user e.g. they are for academic research etc.

Is there any speech to text tool like Dragon Nat in linux? I work as a translator and I have it on windows but I wonder if there is something like that out there.

Baidu is required by Chinese laws to act, as and when demanded, as an arm of the Chinese Communist Party. Not sure I would trust a tool created by them.

I think you are jumping on the Hauwei bandwagon with absolutely no justification.

A few of the open source programs here are using speech recognition models based on Baidu DeepSpeech2. But the model is an approach, not a means of capturing data or doing anything else nefarious.

What concerns are you raising? The source code of the programs here (DeepSpeech etc) are open source, so you can see exactly what they are doing.

completely agree

This account is solely made for saying yes to other accounts called “john”

LinuxLinks doesn’t have accounts

Could Android speech recognition be ported to Linux desktop packages, since android is open source?

Top 11 Open Source Speech Recognition/Speech-to-Text Systems

Last Updated on: March 21, 2024

A speech-to-text (STT) system , or sometimes called automatic speech recognition (ASR) is as its name implies: A way of transforming the spoken words via sound into textual data that can be used later for any purpose.

Speech recognition technology is extremely useful. It can be used for a lot of applications such as the automation of transcription, writing books/texts using sound only, enabling complicated analysis on information using the generated textual files and a lot of other things.

In the past, the speech-to-text technology was dominated by proprietary software and libraries. Open source speech recognition alternatives didn’t exist or existed with extreme limitations and no community around.

This is changing, today there are a lot of open source speech-to-text tools and libraries that you can use right now.

Table of Contents:

What is a Speech Recognition Library/System?

What is an open source speech recognition library, what are the benefits of using open source speech recognition, 1. project deepspeech, 4. flashlight asr (formerly wav2letter++), 5. paddlespeech (formerly deepspeech2), 6. openseq2seq, 10. whisper, 11. styletts2, what is the best open source speech recognition system.

It is the software engine responsible for transforming voice to texts.

It is not meant to be used by end users. Developers will first have to adapt these libraries and use them to create computer programs that can enable speech recognition to users.

Some of them come with preloaded and trained dataset to recognize the given voices in one language and generate the corresponding texts, while others just give the engine without the dataset, and developers will have to build the training models themselves.

You can think of them as the underlying engines of speech recognition programs.

If you are an ordinary user looking for speech recognition, then none of these will be suitable for you, as they are meant for development use only.

The difference between proprietary speech recognition and open source speech recognition, is that the library used to process the voices should be licensed under one of the known open source licenses, such as GPL, MIT and others.

Microsoft and IBM for example have their own speech recognition toolkits that they offer for developers, but they are not open source. Simply because they are not licensed under one of the open source licenses in the market.

Mainly, you get few or no restrictions at all on the commercial usage for your application, as the open source speech recognition libraries will allow you to use them for whatever use case you may need.

Also, most – if not all – open source speech recognition toolkits in the market are also free of charge, saving you tons of money instead of using the proprietary ones.

The benefits of using open source speech recognition toolkits are indeed too many to be summarized in one article.

Top Open Source Speech Recognition Systems

In our article we’ll see a couple of them, what are their pros and cons and when they should be used.

This project is made by Mozilla, the organization behind the Firefox browser.

It’s a 100% free and open source speech-to-text library that also implies the machine learning technology using TensorFlow framework to fulfill its mission. In other words, you can use it to build training models by yourself to enhance the underlying speech-to-text technology and get better results, or even to bring it to other languages if you want.

You can also easily integrate it to your other machine learning projects that you are having on TensorFlow. Sadly it sounds like the project is currently only supporting English by default. It’s also available in many languages such as Python (3.6).

However, after the recent Mozilla restructure, the future of the project is unknown, as it may be shut down (or not) depending on what they are going to decide .

You may visit its Project DeepSpeech homepage to learn more.

Kaldi is an open source speech recognition software written in C++, and is released under the Apache public license.

It works on Windows, macOS and Linux. Its development started back in 2009. Kaldi’s main features over some other speech recognition software is that it’s extendable and modular: The community is providing tons of 3rd-party modules that you can use for your tasks.

Kaldi also supports deep neural networks, and offers an excellent documentation on its website . While the code is mainly written in C++, it’s “wrapped” by Bash and Python scripts.

So if you are looking just for the basic usage of converting speech to text, then you’ll find it easy to accomplish that via either Python or Bash. You may also wish to check Kaldi Active Grammar , which is a Python pre-built engine with English trained models already ready for usage.

Learn more about Kaldi speech recognition from its official website .

Probably one of the oldest speech recognition software ever, as its development started in 1991 at the University of Kyoto, and then its ownership was transferred to as an independent project in 2005. A lot of open source applications use it as their engine (Think of KDE Simon).

Julius main features include its ability to perform real-time STT processes, low memory usage (Less than 64MB for 20000 words), ability to produce N-best/Word-graph output, ability to work as a server unit and a lot more.

This software was mainly built for academic and research purposes. It is written in C, and works on Linux, Windows, macOS and even Android (on smartphones). Currently it supports both English and Japanese languages only.

The software is probably available to install easily using your Linux distribution’s repository; Just search for julius package in your package manager.

You can access Julius source code from GitHub.

If you are looking for something modern, then this one can be included.

Flashlight ASR is an open source speech recognition software that was released by Facebook’s AI Research Team. The code is a C++ code released under the MIT license.

Facebook was describing its library as “the fastest state-of-the-art speech recognition system available” up to 2018.

The concepts on which this tool is built makes it optimized for performance by default. Facebook’s machine learning library Flashlight is used as the underlying core of Flashlight ASR. The software requires that you first build a training model for the language you desire before becoming able to run the speech recognition process.

No pre-built support of any language (including English) is available. It’s just a machine-learning-driven tool to convert speech to text.

You can learn more about it from the following link .

Researchers at the Chinese giant Baidu are also working on their own speech recognition toolkit, called PaddleSpeech.

The speech toolkit is built on the PaddlePaddle deep learning framework, and provides many features such as:

Speech-to-Text support.
Text-to-Speech support.
State-of-the-art performance in audio transcription, it even won the NAACL2022 Best Demo Award ,
Support for many large language models (LLMs), mainly for English and Chinese languages.

The engine can be trained on any model and for any language you desire.

PaddleSpeech ‘s source code is written in Python, so it should be easy for you to get familiar with it if that’s the language you use.

Developed by NVIDIA for sequence-to-sequence models training.

While it can be used for way more than just speech recognition, it is a good engine nonetheless for this use case. You can either build your own training models for it, or use models which are shipped by default. It supports parallel processing using multiple GPUs/Multiple CPUs, besides a heavy support for some NVIDIA technologies like CUDA and its strong graphics cards.

As of 2021 the project is archived; it can still be used but looks like it is no longer under active development.

Check its speech recognition documentation page for more information, or you may visit its official source code page .

One of the newest open source speech recognition systems, as its development just started in 2020.

Unlike other systems in this list, Vosk is quite ready to use after installation, as it supports 10 languages (English, German, French, Turkish…) with portable 50MB-sized models already available for users (There are other larger models up to 1.4GB if you need).

It also works on Raspberry Pi, iOS and android devices, and provides a streaming API which allows you to connect to it to do your speech recognition tasks online. Vosk has bindings for Java, Python, JavaScript, C# and NodeJS.

Learn more about Vosk from its official website .

An end-to-end speech recognition engine which implements ASR.

Written in Python and licensed under the Apache 2.0 license. Supports unsupervised pre-training and multi-GPUs training either on same or multiple machines. Built on the top of TensorFlow.

Has a large model available for both English and Chinese languages.

Visit Athena source code .

Written in Python on the top of PyTorch.

Also supports end-to-end ASR. It follows Kaldi style for data processing, so it would be easier to migrate from it to ESPnet. The main marketing point for ESPnet is the state-of-art performance it gives in many benchmarks, and its support for other language processing tasks such as speech-to-text (STT), machine translation (MT) and speech translation (ST).

Licensed under the Apache 2.0 license.

You can access ESPnet from the following link .

The newest speech recognition toolkit in the family, developed by the famous OpenAI company (the same company behind ChatGPT ).

The main marketing point for Whisper is that it does not specialize in a set of training datasets for specific languages only; instead, it can be used with any suitable model and for any language. It was trained on 680 thousand hours of audio files, one third of which were non-English datasets.

It supports speech-to-text, text-to-speech, speech translation. And the company claims that its toolkit has 50% less errors in the output compared to other toolkit in the market.

Learn more about Whisper from its official website .

The newest speech recognition library on the list, which was just released in the middle of November, 2023. It employs diffusion techniques with large speech language models (SLMs) training in order to achieve more advanced results than other models.

The makers of the model published it along with a research paper, where they make the following claim about their work:

This work achieves the first human-level TTS synthesis on both single and multispeaker datasets, showcasing the potential of style diffusion and adversarial training with large SLMs.

It is written in Python, and has some Jupyter notebooks shipped with it to demonstrate how to use it. The model is licensed under the MIT license.

There is an online demo where you can see different benchmarks of the model: https://styletts2.github.io/

If you are building a small application that you want to be portable everywhere, then Vosk is your best option, as it is written in Python and works on iOS, android and Raspberry pi too, and supports up to 10 languages. It also provides a huge training dataset if you shall need it, and a smaller one for portable applications.

If, however, you want to train and build your own models for much complex tasks, then any of PaddleSpeech, Whisper and Athena should be more than enough for your needs, as they are the most modern state-of-the-art toolkits.

As for Mozilla’s DeepSpeech , it lacks a lot of features behind its other competitors in this list, and isn’t really cited a lot in speech recognition academic research like the others. And its future is concerning after the recent Mozilla restructure, so one would want to stay away from it for now.

Traditionally, Julius and Kaldi are also very much cited in the academic literature.

Alternatively, you may try these open source speech recognition libraries to see how they work for you in your use case.

The speech recognition category is starting to become mainly driven by open source technologies, a situation that seemed to be very far-fetched a few years ago.

The current open source speech recognition software are very modern and bleeding-edge, and one can use them to fulfill any purpose instead of depending on Microsoft’s or IBM’s toolkits.

If you have any other recommendations for this list, or comments in general, we’d love to hear them below!

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Originally published on August 23, 2020, Last Updated on March 21, 2024 by M.Hanny Sabbagh

'ZDNET Recommends': What exactly does it mean?

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How to enable speech-to-text in Linux with this simple app

I'm not a big user of speech-to-text but that's only because I "word" for a living and still have fingers that are capable of typing very fast. That's not something I ever take for granted. And given I've known many people over the years who depended on speech-to-text, I am always very grateful to point out the means to make an operating system more accessible.

So, when I came across the Speech Note app, I was thrilled to find it was quite simple to add speech-to-text in Linux. However, once I installed the app and started using it, I realized that it comes with a considerable caveat…it requires power (and a lot of it).

Also: How to turn on flash notifications on Android 14

The reason this app requires so much power is that speech-to-text processing happens offline, which means it will depend on your CPU (and GPU if you have one) to carry the heavy lifting. If your machine is underpowered, one of two things will happen: the computer will crash while trying to process speech-to-text, or it will happen very slowly. So, if you don't have a powerful desktop computer, you might want to depend on a third-party speech-to-text service, such as that found in Google Docs (which only works with the Chrome browser).

If you have a powerful enough machine, you can turn to the open-source Speech Note app. This app can be installed on any Linux distribution that supports Flatpak . It's important to note, however, that the base installation is very small. However, downloading the language model can take up to 2GB of space, so keep that in mind if your system has limited local storage.

Once installed and ready, Speech Note does a great job of processing speech-to-text on Linux.

Let me show you how to install and prepare Speech Note for use.

How to install Speech Note

What you'll need: To get Speech Note installed, you'll need a Linux machine with Flatpak installed and over 2GB of free internal storage. That's it. Let's make it happen.

1. Open your terminal window and install

Log into your desktop and open the terminal window app. Once the app is open, paste the following command and hit Enter on your keyboard:

Make sure to answer Y to the questions to complete the installation.

2. Open Speech Note

Click your desktop menu and look for the Speech Note launcher. If you don't see it, you might have to log out and log back into your desktop to make it appear.

Speech Note is a simple-to-use GUI app for speech to text on Linux.

3. Download your language model

From the main Speech Note window, click Languages. In the resulting pop-up, locate the language you want to download. Hover over that language and click the associated Download button. When the language model has been downloaded, click Close.

You can download as many language models as you need (so long as your machine has the storage space for it).

4. Configure Speech Note

Click the three-dot menu button in the upper left corner. From the resulting dropdown, click Settings. In the Settings popup, you'll want to consider two changes. The first is the Audio source. Click the dropdown and make sure to select the source associated with your mic. If you're using a built-in mic, you'll probably want to stick Auto. If you're using an external mic, make sure to select it from the list.

Also: Do you need a speech therapist? Now you can consult AI

The next setting is the Listening mode, for which there are three choices: one sentence, press and hold, and always on. One sentence will listen to one sentence at a time. As soon as you stop speaking, Speech Note will stop listening.

Press and hold means it will keep listening as long as you hold the Listen button. Always on means as soon as you click Listen, it will listen and continue to do so until you stop it.

There are a number of configurations you can undertake but these will get you up and running right away.

5. Use Speech Note

Using Speech Note is simple. Click the Listen button and start talking. There will be a lag between your speaking and Speech Notes transcribing. Depending on the speed of your hardware, that lag can be considerable (if the machine is underpowered).

And that's all there is to using the Speech Note app for easy speech-to-text on Linux. Remember, if your machine isn't powerful enough to handle the processing, you can always turn to Google Chrome and Google Docs (which does work quite well on Linux).

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January 21, 2022, nerd-dictation: a fantastic open source speech to text software for linux.

After a long time of searching I finally found a speech to text software for Linux that actually works well enough that I can use it for dictating without having to jump through too many hoops to configure and use. The software is called nerd-dictation and is an open source software. It is fairly easy to setup as compared to the other voice-to-text systems that are available but still not at a stage where a non-tech savvy person would be able to install it easily. (There is effort ongoing to fix that)

The steps to install are fairly simple and documented below for reference:

pip3 install vosk
git clone https://github.com/ideasman42/nerd-dictation.git
cd nerd-dictation
wget https://alphacephei.com/kaldi/models/vosk-model-small-en-us-0.15.zip
unzip vosk-model-small-en-us-0.15.zip
mv vosk-model-small-en-us-0.15 model

nerd-dictation allows you to dictate text into any software or editor which is open so I can dictate into a word document or a blog post or even the command prompt. Previously I have used tried using software like otter.ai which actually works quite well but doesn’t allow you to edit the text as you’re typing, so you basically dictate the whole thing and the system gives you the transcription after you are done. So, you have to go back and edit/correct the transcript which can be a pain for long dictations. This software works more like Microsoft dictate which is built into Word. Unfortunately my word install on Linux using Crossover doesn’t allow me to use the built in dictate function and I have no desire to boot into windows just so that I can dictate a document.

This downloads the software in the current directory. I set it up on /usr/local but it is up to you where you want it. In addition, I would recommend that you install one of the larger dictionaries/models which makes the voice recognition a lot more accurate. However, do keep in mind that the larger models use up a lot more memory so you need to ensure that your computer has enough memory to support the larger models. The smaller ones can run on systems as small as a raspberry pi, so depending on your system configuration you can choose. The models are available here .

The software does have some quirks, like when you are talking and you pause it will take it as a start of a new sentence and for some reason it doesn’t put a space after the last word. So unless you’re careful you need to go back and add spaces to all the sentences that you have dictated, which can get annoying. (I started manually pressing space everytime I paused to add the space). Another issue is that it doesn’t automatically capitalize the words when you dictate such as those at the beginning of the sentence or the word ‘I’. This requires you to go back and edit, but that being said it still works a lot better than the other software that I have used so far on Linux. For Windows system Dragon Voice Dictation works quite well but is expensive. I tested it out by typing out this post using it and for the most part it does work it worked quite well.

Running the software again requires you to run commands on the commandline, but I configured shortcut keys to start and stop the dictation which makes it very convenient to use. Instructions on how to configure custom shortcut keys are available here . If you don’t want to do that, then you can start the transcription by issuing the following command (assuming the software is installed in /usr/local/nerd-dictation):

This starts the software and tells it that we are going to dictate for a long time. More details on the options available are available on the project site. To stop the software you should run the following command:

I suggest you try this if you are looking for a speech-to-text software for Linux. Well this is all for now. Will post more later.

Thanks to Hacker News: Nerd-dictation, hackable speech to text on Linux for the link.

– Suramya

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Ubuntu Speech-to-Text Tutorial

We love Ubuntu at Picovoice. Our standard dev machines are running Ubuntu. No offence to macOS and Windows fans 😉

Today you can run Ubuntu on a single-board computer (SBC) like Raspberry Pi, NVIDIA Jetson, or BeagleBone. At the same time, one can have it on a server or a desktop. Below we look at options for running Speech-to-Text on an Ubuntu machine. Then we dive deeper into how to run Picovoice Leopard Speech-to-Text Engine on Ubuntu.

Speech-to-Text on Ubuntu

You can use any API: Google Speech-to-Text, Amazon Transcribe, IBM Watson Speech-to-Text, or Azure Cognitive Services Speech-to-Text. The downside? They are pretty expensive for anything other than a proof of concept but are relatively accurate. Additionally, you need to send raw audio data to the cloud, which means extra power consumption and bandwidth cost. The latter is only a concern if you are on a cellular connection.

Alternatively, you can use free and open-source (FOSS) software. Kaldi (derivations of such as Vosk), Mozilla DeepSpeech (derivations of such as Coqui), and many more. The upside is that they are free, but the downside is that they hardly match the accuracy of API-based ASRs nor have all the features you might require (e.g. custom words and keyword boosting). If you care about the runtime efficiency, they are not necessarily optimized. These can be good starting points if you decide to build your own.

Picovoice Leopard Speech-to-Text processes voice locally on the device while matching the accuracy of API alternatives from Big Tech. Developers can start transcribing in seconds with Picovoice’s Free Plan , even for commercial projects.

Leopard comes with a total package size of 20MB (compared to GBs of FOSS alternatives). Leopard runtime efficiency enables it to run even on Raspberry Pi 3 using only a quarter of only one of the CPU cores.

Leopard Python SDK

Install Leopard Python package using PIP:

Sign up for Picovoice Console and copy your AccessKey to the clipboard. AccessKey handles authentication and authorization.

Create an instance of Leopard STT and transcribe a file:

Node.js, Rust, Go, Java, .NET, ...

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Speech Note Transcribes Voice to Text on Linux

Posted by by Scott Bouvier
August 28, 2023

Speech Note is an offline, AI-powered app able to transcribe your speech into text in a variety of different languages.

A reader got in touch to point me towards the app — thanks, David! — and given that it sounds pretty cool I figured I’d give it a spotlight on the site.

Speech Note use OpenAI’s Whisper and a stack of other open-source libraries, voice engines, and other doohickeys to perform its transliterative magic.

It supports Speech to Text (i.e you speak, it types), Text to Speech (i.e. you type, it speaks), and machine translation to translate text/speech from one language to another.

“Text and voice processing take place entirely offline, locally on your computer, without using a network connection. Your privacy is always respected. No data is sent to the Internet,” assures the application’s Flathub listing.

Those with a supported GPU will want to turn GPU acceleration on as will hugely improve processing times (which are on the slow side if only using CPU processing).

Speech Note is a 620MB download from Flathub (excluding any runtimes or platforms required) and takes up around ~2GB when installed – if you’re data or disk constrained, do keep those factors in mind.

• Get Speech Note on Flathub

Home > Apps > Speech Note Transcribes Voice to Text on Linux

Scott Bouvier

An international man of mystery, Scott enjoys personal computing, mobile technology, and outdoor pursuits. He once went wing-walking on a biplane over London – scary, huh?

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Speech Note Linux app. Note taking, reading and translating with offline Speech to Text, Text to Speech and Machine translation.

mkiol/dsnote

Folders and files, repository files navigation, speech note.

Linux desktop and Sailfish OS app for note taking, reading and translating with offline Speech to Text, Text to Speech and Machine Translation

Contents of this README

Description, languages and models, how to install, flatpak packages, beta version, building from sources, how to enable a custom model, contributing to speech note, how to support, reviews and demos.

Speech Note let you take, read and translate notes in multiple languages. It uses Speech to Text, Text to Speech and Machine Translation to do so. Text and voice processing take place entirely offline, locally on your computer, without using a network connection. Your privacy is always respected. No data is sent to the Internet.

Speech Note uses many different processing engines to do its job. Currently these are used:

Coqui STT (a fork of Mozilla DeepSpeech)
whisper.cpp
Faster Whisper
WhisperSpeech
Bergamot Translator

Following languages are supported:

(e) experimental, most likely doesn't work well

Faster Whisper, Coqui TTS and Mimic3 models are only available on x86-64.

Language models can be downloaded directly from the app.

Details of models which are currently configured for download are described in models.json (GitHub) or models.json (GitLab) .

Linux Desktop: Flatpak
Sailfish OS: OpenRepos

Starting from v4.4.0, the app distributed via Flatpak (published on Flathub) consists of the following packages:

Base package "Speech Note" (net.mkiol.SpeechNote)
Add-on for AMD graphics card "Speech Note AMD" (net.mkiol.SpeechNote.Addon.amd)
Add-on for NVIDIA graphics card "Speech Note NVIDIA" (net.mkiol.SpeechNote.Addon.nvidia)

Base package includes all the dependencies needed to run every feature of the application. Add-ons add the capability of GPU acceleration, which speeds up some operations in the application.

Base package and add-ons contain many "heavy" libraries like CUDA, ROCm, Torch and Python libraries. Due to this, the size of the packages and the space required after installation are significant. If you don't need all the functionalities, you can use much smaller "Tiny" package (available on Releases page), which provides only the basic features. If you need, you can also use "Tiny" packages together with GPU acceleration add-on.

Comparison between Base, Tiny and Add-ons Flatpak packages:

In addition to the stable version in the Flathub repository, you can try to test the "Beta" version of the upcoming release. This version is usable, but may contain more bugs.

Beta version is available in "flathub-beta" repository. Follow these instructions to enable flathub-beta on your computer.

It is also possible to build and install the latest development (git) or latest stable (release) version from the repository using the provided PKGBUILD file (please note that the same remarks about building on Linux apply):

Sailfish OS

Linux (direct build).

Speech Note has many build-time and run-time dependencies. This includes shared and static libraries, 3rd-party executables, Python and Perl scripts. Because of these complexity, the recommended way to build is to use Flatpak tool-chain (Flatpak manifest file and flatpak-builder ). If you want to make a direct build (i.e. without flatpak) it is also possible but more complicated.

To make build without support for Python components, add -DWITH_PY=OFF in cmake step.

To see other build options search for option(BUILD_XXX) in CMakeList.txt file.

All models available for download are specified in the configuration file (config/models.json). To enable a custom model that is compatible with currently supported engines, simply edit this file and restart the application.

When you first run the application, the models configuration file is created in:

~/.local/share/net.mkiol/dsnote/models.json , or
~/.var/app/net.mkiol.SpeechNote/data/net.mkiol/dsnote/models.json (Flatpak), or
~/.local/share/org.mkiol/dsnote/models.json (Sailfish OS)

You can freely edit currently enabled models or add new ones.

Model definition looks like this:

Allowed engine types: stt_ds , stt_vosk , stt_april , stt_whisper , stt_fasterwhisper , tts_piper , tts_rhvoice , tts_espeak , tts_coqui , tts_mimic3 , mnt_bergamot

Allowed compression types: none , gz , xz , tarxz , targz , zip , zipall , dir , dirgz

Allowed URL types: http , https , file

Checksums are calculated for all files after unpacking. If you are adding a new model, you can use the --gen-checksums command line option to find the right checksums. To do this, put empty strings in both checksum and checksum_quick , save the file and run Speech Note with the mentioned option.

For example:

Any contribution is very welcome!

Project is hosted both on GitHub and GitLab . Feel free to make a PR/MR, report an issue or reqest for new feature on the platform you prefer the most.

Translation

Translation files in Qt format are in translations directory.

Preferred way to contribute translation is via Transifex service , but if you would like to make a direct PR/MR, please do it.

If you find Speech Note useful and would like to support this project, please consider doing one or two of the following:

Give a ⭐ on GitHub or/and GitLab .
Write a review in your applications manager app (Discover, Software or any other).
Tell others about this app by mentioning it on social media.
If you have spare money, make a small donation via Liberapay .

Speech Note relies on following open source projects:

Hugging Face Transformers
bergamot-translator
Rubber Band Library
Nlohmann JSON
libnumbertext
KDBusAddons
faster-whisper
Screenshots (Speech Note 4.4)
alternativalinux (Speech Note 4.4, Italian)
alternativalinux video (Speech Note 4.4, Italian)
ZDNET (Speech Note 4.2)
Translator feature video demo on Sailfish OS (Speech Note 4.0)
Translator feature video demo on PinePhone (Speech Note 4.0)
DebugPoint.com (Speech Note 4.0)
DebugPoint.com video (Speech Note 4.0)
OMG! Linux (Speech Note 4.0)
LinuxLinks (Speech Note 4.0)
The Linux Cast video (Speech Note 4.0)
CONNECTwww.com (Speech Note 4.0)

Speech Note is an open source project. Source code is released under the Mozilla Public License Version 2.0 .

3rd party libraries:

Coqui STT , released under the Mozilla Public License Version 2.0
Coqui TTS , released under the Mozilla Public License Version 2.0
Vosk API , released uder the Apache License 2.0
whisper.cpp , released under the MIT License
WebRTC , released under this license
libarchive , released under the BSD License
RNNoise-nu , released under the BSD 3-Clause License
{fmt} , released uder this license
Hugging Face Transformers , released under the Apache License 2.0
Piper , released under the MIT License
RHVoice , released under the GNU General Public License v2.0
ssplit-cpp , released under the Apache License 2.0
espeak-ng , released under the GNU General Public License v3.0
bergamot-translator , released under the Mozilla Public License 2.0
Rubber Band Library , released under the GNU General Public License (version 2 or later)
simdjson , released under the Apache License 2.0
Nlohmann JSON , released under the MIT License
uroman , released under this license
astrunc , released under the MIT License
FFmpeg , released under the GNU Lesser General Public License version 2.1 or later
LAME , released under the LGPL
Vorbis , released under this license
TagLib , released under the GNU Lesser General Public License (LGPL) and Mozilla Public License (MPL)
libnumbertext , released under the BSD License
KDBusAddons , released under the LGPL licenses
QHotkey , released under the BSD-3-Clause License
faster-whisper , released under the MIT License
Mimic 3 , released under the AGPL-3.0 license
Unikud , released under the MIT License
april-asr , released under the GNU General Public License v3.0
libopus , released under this license
html2md , released under the MIT License
maddy , released under the MIT License
WhisperSpeech , released under the MIT License

The files in the directory nonbreaking_prefixes were copied from mosesdecoder project and distributed under the GNU Lesser General Public License v2.1 .

Releases 15

Contributors 9.

Speech Note Transcribes Voice to Text on Linux

Speech Note is an offline, AI-powered app able to transcribe your speech into text in a variety of different languages.

A reader got in touch to point me towards the app — thanks, David! — and given that it sounds pretty cool I figured I’d give it a spotlight on the site.

Speech Note use OpenAI’s Whisper and a stack of other open-source libraries, voice engines, and other doohickeys to perform its transliterative magic.

It supports Speech to Text (i.e you speak, it types), Text to Speech (i.e. you type, it speaks), and machine translation to translate text/speech from one language to another.

Those with a supported GPU will want to turn GPU acceleration on as will hugely improve processing times (which are on the slow side if only using CPU processing).

• Get Speech Note on Flathub

The post Speech Note Transcribes Voice to Text on Linux is from OMG! Linux and reproduction without permission is, like, a nope.

Source: OMG! Linux

Speech Note

Note taking, reading and translating with offline speech to text, text to speech and machine translation.

Changes in version 4.4.0

Modular Flatpak package. The application package is divided into a base package 'Speech Note' (net.mkiol.SpeechNote) and two optional add-ons: 'Speech Note AMD' (net.mkiol.SpeechNote.amd) and 'Speech Note NVIDIA' (net.mkiol.SpeechNote.nvidia). Add-ons packages provide a set of libraries for GPU acceleration with AMD and NVIDIA graphics cards. New "modular" approach makes the base Flatpak package much smaller.
NVIDIA CUDA runtime update to version 12.2
AMD ROCm runtime update to version 5.6
PyTorch update to version 2.1.1

User Interface:

Improvements to the model browser. You can check various model properties such as size, license, and the URLs from which the model is downloaded.
Model filtering options. Models can be searched by various features such as: Processing speed, Quality, Additional capabilities.
Setting option to minimize to the system tray
Setting option to enable/disable including of recognized or read text in desktop notifications

Speech to Text:

Marathi language. New language is enabled with Whisper and Faster Whisper models.
New version of Faster Whisper Large model: 'FasterWhisper Large-v3'
New 'Distil' Faster Whisper models for English. 'Distil' models are potentially faster than regular models.
Whisper and Faster Whisper enabled for Chinese-Cantonese language
Support for Speex audio codec in 'Transcribe a file'
Translate to English option for Whisper and Faster Whisper models
More effective GPU acceleration for Whisper models with AMD graphics cards
Subtitles generation
Support for multiple audio streams in a video file

Text to Speech:

Marathi language. New language is enabled with Coqui MMS model.
Voice cloning with Coqui XTTS and YourTTS models. Coqui XTTS models are enabled for: Arabic, Brazilian Portuguese, Chinese, Czech, Dutch, English, French, German, Hungarian, Italian, Japanese, Korean, Polish, Russian, Spanish and Turkish. Coqui YourTTS model is enabled for: English, French and Brazilian Portuguese.
Voice samples creator. A reference voice sample is used for voice cloning. You can create voice sample with a microphone or from audio or video file. The sample creator is available on main toolbar only if the selected TTS model supports voice cloning.
New voices for Serbian and Uzbek languages (RHVoice models)
GPU acceleration for Coqui models with AMD graphics cards
Speech synchronized with subtitle timestamps (e.g. useful for voice overs)

Translator:

New model: Lithuanian to English
Option to force text cleaning before translation. If the input text is incorrectly formatted, this option may improve the translation quality.
Text formatting support. The translation will preserve the formatting from the input text. Supported formats are: HTML, Markdown and SRT Subtitles.
Translation progress indicator
Setting option to override GPU version (AMD graphics cards)
Setting option to limit number of simultaneous CPU threads
Setting option to set Python libraries directory (PYTHONPATH). This option may be useful if you use 'venv' module to manage Python libraries.
Potentially unsafe User device access; Download folder read/write access; Can access some specific files; Uses an end-of-life runtime

Community built

Other apps by michal kosciesza.

eSpeak: Text To Speech Tool For Linux

eSpeak is a command line tool for Linux that converts text to speech. This compact speech synthesizer provides support for English and many other languages. It is written in C.

eSpeak reads the text from the standard input or input file. The voice generated, however, is nowhere close to a human voice. But it is still a compact and handy tool if you want to use it in your projects.

Some of the main features of eSpeak are:

Speaks text from a file or from stdin
Shared library version to be used by other programs
SAPI5 version for Windows, so it can be used with screen-readers and other programs that support the Windows SAPI5 interface
Ported to other platforms, including Android, Mac OSX etc.
Several voice characteristics to choose from
Speech output can be saved as .WAV file
SSML ( Speech Synthesis Markup Language ) is supported partially along with HTML
Uses a “formant synthesis” method. This allows many languages to be provided in a small size.
Tiny in size, the complete program with language support, etc is under 2 MB.
Can translate text into phoneme codes so that it could be adapted as a front end for another speech synthesis engine.
Development tools are available for producing and tuning phoneme data
Supports several languages; however, in many cases these are initial drafts and need more work

Install eSpeak

To install eSpeak in Ubuntu based system, use the command below in a terminal:

eSpeak is an old tool and I presume that it should be available in the repositories of other Linux distributions such as Fedora. You can install eSpeak easily using the respective package manager. I

n case of Arch Linux, the repository has espeak-ng in place, which is described in the next section.

To use eSpeak, enter espeak in the terminal. It waits for input. You can start typing your text. When you press enter (new line), you can hear the text you had entered.

You can continue adding text in lines to hear it out. Use Ctrl+C to close the running program .

There are several other options available. You can browse through them through the help section of the program.

espeak help section explaining the usages

GUI Version: espeakedit

If you prefer the GUI version over the command line, you can install espeakedit which provides a GTK front end to eSpeak.

Use the command below to install espeakedit:

Once installed, you need to copy the data on /usr/lib/x86_64-linux-gnu/espeak-data/ to your home directory. For this, open a terminal and run:

Once done, you can open the espeakedit application. It will look like:

You can enter the text on the field provided and press speak to start. You can save the file as .WAV file and listen later.

The interface is straightforward and easy to use. You can explore the submenus and functions all by yourself.

A New Tool: eSpeak NG

The eSpeak NG is a compact open-source text-to-speech synthesizer, based on eSpeak engine created by Jonathan Duddington.

It offers the features of eSpeak and is in active development. The project also provides a separate espeak-ng-data package, to avoid conflict with the espeak-data package offered by eSpeak project.

To install this, on Ubuntu, run:

The new eSpeak NG project is a significant departure from the eSpeak project, aiming to clean up the existing codebase, add new features, and add to and improve the supported languages.

Also, it is important to note that espeakedit GUI is not part of this new project.

Some of the notable features:

Uses the same command-line options as espeak with several additions.
Provides new functionality such as specifying the output audio device name to use.
Has been ported to other platforms, including Solaris and Mac OSX.
Includes different voices whose characteristics can be altered.
Available as a command-line program for Linux and Windows to speak text from a file or from stdin.
Available as a shared library version for use by other programs.

Wrapping Up

On It’s FOSS, we use Play.ht to provide audio formats of selected articles. The espeak tools are not as good as the professional AI tools.

However, if you want something basic and free to be used in your project, you can give it a try.

Abhishek Prakash

Created It's FOSS 11 years ago to share my Linux adventures. Have a Master's degree in Engineering and years of IT industry experience. Huge fan of Agatha Christie detective mysteries 🕵️‍♂️

Meet DebianDog - Puppy sized Debian Linux

Reduce computer eye strain with this nifty tool in linux, install open source dj software mixxx version 2.0 in ubuntu, install adobe lightroom alternative rawtherapee in ubuntu linux, complete guide to installing linux on chromebook, it's foss.

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Linux and Dev Portal

Speech Recognition to Text in Linux, Ubuntu using Google Docs

This is how you can convert speech to text in Linux systems, including Ubuntu.

There is not much speech recognition software available in Linux systems, including native desktop apps. There are some apps available that use IBM Watson and other APIs to convert speech to text, but they are not user-friendly and require an advanced level of user interactions, e.g. a little bit of programming or scripting in respective languages.

However, not many users know that Google Docs provides an advanced level of Speech Recognition using its own AI technologies, which can be accessed via Chrome in Google Docs.

Any user can use this feature to convert speech to text, requiring no advanced level of computer knowledge. The best thing about this feature of Google Docs is you can use it in any Ubuntu derivatives or any Linux distribution where Chrome is available.

Let’s take a look at how you can enable it in Ubuntu.

Table of Contents

How to convert speech to text

The prerequisites are having Chrome installed in your system and a Google account. You can visit this page for the Chrome installation guide if you don’t have Chrome installed.

Also, if you don’t have a Google account, you can create one using this link for free.

Step 1: Open Google Docs

Open https://docs.google.com from Chrome and create a blank document.

Step 2: Launch Voice Typing

After the blank document is loaded, click Tools > Voice typing from the menu.

Step 3: Click on speak button

On the left-hand side, you can see a microphone icon. Click the microphone icon. Google Chrome will ask for microphone permission first time. Hit Allow to give access.

By default, it uses your system language as the detecting language of voice while converting it into the text; however, you can change it to any language you want per the available list of languages. So far, more than 60+ languages are supported and recognized in Google Docs while converting them to text.

Step 4: Speak and record

After you click allow, the microphone icon will turn orange, and now it’s ready to accept or recognize your voice. Start speaking anything you want, and voila! You will see your speech is being converted to text and written in the document.

That’s it. You have successfully converted voice to text in Ubuntu via Google Chrome and Google docs.

This amazing feature is available for all Linux users for free. Drop a comment below using the comment box if you are aware of other apps that can convert voice to text in Linux. Also, let me know whether you found this helpful article.

Troubleshooting

1. If the above feature is not working in your browser, make sure to check out the following.

Open the Settings window (in GNOME desktop in Ubuntu or another distro).
Go to Privacy > Microphone .
And make sure it’s enabled.

2. Since many users reported about problem with the above method in Linux Mint, I have tried and it works perfectly in Linux Mint (Tried in 21). However, you need to change sound settings, because for some reason Linux Mint input mic sound is muted by default!

Open “Sound” from the menu.
Then go to “Input” tab. Under device settings, increase the volume to 100% to louder.

Close the window and it will now work in Linux Mint.

Wrapping Up

Although, there is a cloud-based solution available recently, such as Amazon Polly and others. But they come with a steep price. Plus requires a bit of useful knowledge as well.

Whereas Google Chrome’s built-in speech recognition feature is simple and easy to use. It can get the job done for average users, although it’s a little slow.

That said, I hope this guide helps you to convert voice to text and do let me know in the comment box if you know of such an application which does the same for free.

Posted by Arindam

This site uses Akismet to reduce spam. Learn how your comment data is processed .

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An In-Depth Guide to Open Source Text-to-Speech Engines for Linux

This comprehensive guide explores the top open source text-to-speech (TTS) engines available for Linux. Converting text into lifelike speech is useful for accessibility, delivering information via voice interfaces, learning pronunciation, and more. We’ll cover the capabilities of leading Linux TTS tools, their installation, and plenty of usage examples.

Introduction to Text-to-Speech

Text-to-speech (TTS) is the artificial production of human speech from written text. TTS engines ingest text, process it through natural language pipelines, and output synthesized audio speech. The quality of TTS systems is determined by how natural and humanlike the generated voices sound.

TTS has many practical use cases:

Improving accessibility for vision-impaired users
Reading text aloud when eyes-free is needed like while driving
Delivering information over voice interfaces or phone systems
Assisting with learning languages and proper pronunciation
Transcribing documents to audio book format
Adding speech output to applications by leveraging TTS APIs

High-quality voices require sophisticated deep learning algorithms. Most modern TTS engines utilize machine learning trained on huge datasets of recorded human speech.

In this guide, we’ll focus on open source command line utilities for performing TTS on Linux. Let‘s look at some of the best options.

eSpeak – Lightweight Open Source TTS

eSpeak is an open source text-to-speech engine released in 1995 by Jonathan Duddington. It supports over 70 languages and accents and is highly configurable for adjusting speech parameters.

eSpeak is lightweight and designed to be portable across many systems. It comes bundled with many Linux distributions due to being open source (GPLv3 license). The voices tend to sound robotic but the speech is clear and works well.

To install on Debian/Ubuntu:

Arch Linux:

Basic usage is simple. To output text to speech:

To read a file aloud:

Let‘s go through some ways to customize and control eSpeak‘s voices.

To list all available voices:

This prints out a table summarizing each voice‘s language, dialect, and identifier.

For example, to set the voice to US English:

Adjust the speech rate with the -s flag:

The pitch can be adjusted with -p :

To save audio output to a file, use -w :

This saves a Wave audio file that can be played in media players. eSpeak supports outputting .wav , .mp3 , and .ogg .

In addition to these common uses, eSpeak provides phoneme support for precise pronunciation:

And an API for integrating TTS directly into applications with C, C++, Python and other languages.

Overall, eSpeak provides a capable open source text-to-speech system on Linux. The voices aren‘t as human sounding as some commercial options, but it‘s free, customizable, lightweight, and easy to use.

Festival – Framework for Building TTS Voices

Festival is another leading open source text-to-speech system originally developed at the University of Edinburgh and released in 1997.

Festival utilizes a modular framework for building synthetic voices. It comes packaged with several English voices and support for Spanish, Welsh, and other languages. Festival is well-suited for research and education purposes.

Install Festival using your Linux distribution‘s package manager:

Some example usage:

Festival includes an interactive shell for experimenting with speech synthesis. This allows modifying parameters on the fly:

Under the hood, Festival provides a framework for building TTS voices called FestVox. This allows developers to create new synthetic voices and languages.

For basic usage, Festival has clear text-to-speech capabilities but sounds robotic. The option to build custom voices is useful for research. However, modern TTS technology has surpassed Festival‘s voice quality.

Pico TTS – Optimized Small Footprint Engine

Pico TTS is an open source project to create a small footprint text-to-speech engine optimized for embedded Linux.

The engine itself is written in C++ and comes packaged in many Linux distributions. It‘s licensed under the LGPL and was originally developed for the Raspberry Pi.

Install on Debian/Ubuntu:

Pico TTS supports English, Spanish, French, German, and Italian voices. Since it‘s designed for small systems, the quality is surprisingly good for the small resource requirements.

To synthesize text and save as a WAV file:

Here -l specifies the language code like en-US for US English.

Pico TTS doesn‘t allow piping text directly to stdout. But the WAV output works well for offline usage.

In summary, Pico TTS provides a capable text-to-speech engine optimized for embedded Linux applications like the Raspberry Pi. For desktop use, other options might be higher quality. But as a small footprint engine, Pico TTS works quite well.

gTTS – Leveraging Google‘s TTS API

gTTS provides a command line interface and Python library for Google Translate‘s Text-to-Speech API. It‘s an easy way to access Google‘s state-of-the-art deep learning models.

gTTS can be installed with pip:

Or on Linux distributions:

Basic usage:

This saves the synthesized audio to an MP3 file.

To read a text file aloud:

gTTS supports dozens of languages and natural sounding voices provided by Google:

Prints out all the available languages and voice codes.

For example, set the language to US English:

gTTS is ideal way to leverage Google‘s industry leading text-to-speech engine from the Linux command line. The audio quality is human sounding and highly intelligible.

Comparing Voice Quality Between TTS Engines

There are noticeable differences in audio quality between the open source text-to-speech solutions we covered. Let‘s do a quick comparison.

eSpeak and Festival sound robotic since they rely on formant synthesis instead of deep learning. eSpeak voices tend to be clearer than Festival.

Pico TTS delivers good quality given its tiny resource footprint. The voices aren‘t perfectly human sounding but quite intelligible.

gTTS provides the most natural sounding audio by far since it uses Google‘s state-of-the-art WaveNet deep neural network voices. The quality difference is very noticeable.

For the best sounding voices, gTTS is recommended. But the open source engines like eSpeak work well enough for some use cases, especially considering they‘re free.

Additional Tips and Tricks

Here are some additional tips for getting the most out of Linux text-to-speech engines:

Adjust speech rate, pitch, and volume to customize the voice
Use phoneme support for precise pronunciation of texts
Output audio to a file instead of directly to speakers
Pipe audio to media players like mplayer for enhanced controls
Chain multiple engines together for more options
Install alternative voices and languages
Use TTS engines from other languages like Chinese, Russian, etc.
Integrate speech synthesis directly into your own apps with provided APIs

And some troubleshooting advice:

If no audio, check speakers are not muted and volume is up
Install any required audio codec packs for your system
Try a different TTS engine if issues with a specific one
Look for error output for diagnose problems
Consult documentation and GitHub issues page

With a bit of tweaking, the open source text-to-speech engines provide plenty of options for your Linux projects.

Leveraging TTS Engines in Shell Scripts

One useful application of text-to-speech on Linux is scripting batch text file conversions. Here is an example bash script to synthesize all text files in a directory using eSpeak:

This iterates through .txt files, converts each to audio with eSpeak using the -w flag, and saves the output as a .wav file.

Scripts like this provide an easy way to automate batch text-to-speech conversions and workflows.

Appendix: Quick Reference of Engines

This guide covered several excellent open source text-to-speech utilities for Linux. eSpeak and Festival are classic options that work reasonably well. Pico TTS is great for embedded devices. gTTS provides the best sounding human voices by leveraging Google‘s technology.

The installation process, basic usage, and customization options were explained for each text-to-speech engine. TTS enables many exciting applications on the Linux command line and within scripts or apps.

To learn more about the capabilities of each text-to-speech engine, be sure to consult the official project documentation. Their GitHub repositories also contain useful code samples to get started.

With the power of text-to-speech, Linux can talk back to you! Converting text to natural sounding speech opens many possibilities.

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How to use whatsapp from your desktop or laptop.

Take your chats to a bigger screen

WhatsApp is a multi-faceted app that lets you message your loved ones, place voice or video calls, send documents, and media either from your smartphone or a desktop. WhatsApp's linked devices support allows you to use the service on up to four devices without connecting your main phone. It works on WhatsApp for the web, Windows, Mac, and Android to use the same WhatsApp accounts on two phones .

WhatsApp can also be used on your favorite Chromebook . However, apart from using WhatsApp web, you can use the WhatsApp desktop app or the web version to stay in touch with friends and family. Let's understand how you can use WhatsApp from your desktop or laptop.

Getting started with WhatsApp desktop

WhatsApp has steadily improved the desktop app with new features. You can download the WhatsApp app for Mac or Windows . WhatsApp has a clean interface and also comes with calling features, just like the smartphone app. Besides, Meta launched the macOS app in August, after testing it in public beta for some time .

Whether you download WhatsApp from the Microsoft Store or the Mac App Store, the setup process mostly remains the same.

Set up WhatsApp desktop using your Android phone

1. Open WhatsApp on your desktop or Mac running macOS.

2. On your Android phone, open WhatsApp , and then go to the three-dot menu ( ⋮ ) in the upper-right corner and select Linked devices .

3. Tap the Link a device button, authenticate your identity, and point your phone at the QR code on your desktop or laptop screen.

4. Once you've done that, and after some loading, your WhatsApp messages appear on your computer.

5. You can repeat the process on four other devices, letting you text from all of them simultaneously.

Set up WhatsApp desktop using your iPhone

Since WhatsApp for iOS uses a different interface, the steps to change a QR code vary on it.

1. Open the WhatsApp mobile app on your iPhone and go to Settings .

2. Select Linked Devices .

3. Tap Link a Device .

4. Authenticate with Face ID or Touch ID and scan the QR code using the default camera.

Use WhatsApp Web

WhatsApp works through your web browser, such as Google Chrome, and doesn't need to be installed. It's convenient if you use a work computer and your administrator doesn't allow you to install apps. It's also perfect if you use a Chromebook or a Linux-based system.

Here's how to set up WhatsApp on the web.

1. Visit web.whatsapp.com on your preferred desktop browser.

2. Open the Linked Devices menu on your Android or iPhone (check the steps above).

3. Capture the displayed QR code on the screen.

4. Turn on notification permission for WhatsApp. Click the lock icon in the address bar and open Site settings .

5. Expand Notifications and select Allow .

You can use the same trick to use WhatsApp on an iPad or an Android tablet.

WhatsApp for desktop features

WhatsApp for desktops isn't an afterthought from the company. It's packed with useful features.

Make voice calls with up to 32 people and video calls with up to 8 people simultaneously.
Excellent support for keyboard shortcuts to navigate the app like a pro.
Pin up to three important chats at the top.
Check communities and view status updates.
Stickers, GIFs, and voice messages support.
Access all privacy options (unavailable on new WhatsApp apps).
Rich theme support.
View your entire WhatsApp call history.
Join the group call after it has started.
Receive notifications even if your phone is offline.
Share media and documents by simply dragging and dropping into a chat.

WhatsApp for desktop limitations

WhatsApp for desktops comes with certain limitations.

It doesn't display all your past messages. You may be required to use your phone to check the chat history. However, it shows more message history than the WhatsApp web.
You can't export WhatsApp chat on the desktop.
You can't share your location from the desktop app.
You can't add an unknown number to contacts.

WhatsApp Web vs. WhatsApp desktop

If you want a mobile experience on Windows or Mac, go with the desktop apps. They work well with system notifications, and you can launch WhatsApp at device startup. If you have a low-end Windows laptop or MacBook, we recommend going with the web version since it consumes less CPU energy on the device. They both cover the basics of text messaging and media sharing.

How to unlink WhatsApp web or desktop

If you need to unlink a device from your WhatsApp account, revoke access from your phone, which is helpful if your computer is stolen or you forget to lock it. Here's how to do it:

Unlink WhatsApp on Android

1. Open WhatsApp on your mobile device.

2. Tap the three-dot menu ( ⋮ ) in the upper-right corner and select Linked devices .

3. Tap the device you wish to unlink.

4. Confirm your selection by tapping Log Out .

Unlink WhatsApp on iPhone

iPhone users can follow the steps below to remove device access.

1. Open Linked Devices in iPhone Settings (check the steps above).

2. Select your linked device.

3. Check the platform and the last active date and time. Tap it and select Log Out .

Enjoy texting from your computer

Both the desktop and web apps offer the same WhatsApp chat features you're familiar with. However, the PC version lets you attach and send files from your PC. Besides, typing on a desktop keyboard is easier than on a smartphone. You can also keep other tabs open alongside WhatsApp on the screen and copy and paste information into your chat messages. The desktop apps also support the top WhatsApp privacy features to keep prying eyes away from your account.

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Senate Passes TikTok Ban Bill, Setting Up Legal Battle Between App and U.S. on First Amendment Issues

Legislation to force China's ByteDance to divest TikTok was tied to foreign-aid package; President Biden has said he will sign TikTok bill into law

By Todd Spangler

Todd Spangler

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The U.S. Senate voted Tuesday to approve a bill that would ban TikTok nationwide unless Chinese parent company ByteDance sells its stake in the popular app. The development will likely result in a court battle between the U.S. and TikTok, which argues that the legislation violates the First Amendment — and if TikTok loses that fight, there’s a real chance it could be shut off for Americans.

Popular on Variety

TikTok will file a legal challenge once the bill is signed into law , Michael Beckerman, TikTok’s head of public policy for the Americas, wrote in a memo to company staff over the weekend. The legislation is a “clear violation” of the First Amendment, the exec wrote: “This is the beginning, not the end of this long process.” Beckerman also criticized the TikTok divest-or-ban measure as “an unprecedented deal worked out between the Republican Speaker [Mike Johnson] and President Biden.”

Ahead of the vote, Sen. Mark Warner (D-Va.), chair of the Senate Intelligence Committee, delivered comments on the Senate floor Tuesday afternoon about the national security threats posed by ByteDance’s ownership of TikTok. Passage of the bill “goes a long way towards safeguarding our democratic systems from covert foreign influence,” he said, saying that Chinese companies like ByteDance “don’t owe their obligation to their customers, or their shareholders, but they owe it to the PRC [People’s Republic of China] government.”

Sen. Maria Cantwell (D-Wash.), chair of the Senate’s Commerce, Science and Transportation Committee, suggested TikTok and ByteDance are “weaponizing” data and AI to spy on American citizens, the military and government personnel, including journalists covering the company. (In 2022, ByteDance said it fired four employees for “misconduct” after the company found they accessed TikTok data on several users , including two reporters.)

Sen. Ed Markey (D-Mass.) spoke out against the TikTok ban bill before the final vote, saying the more pressing “clear and present danger” is the harm kids face from social media apps more broadly, including from U.S.-based companies.

“I don’t deny that TikTok poses some national security risks,” Markey said. “TikTok has its problems. No. 1, TikTok poses a serious risk to the privacy and mental health of our young people.” But he said the bill likely would result in “widespread censorship,” and he suggested that the bill’s supporters object to liberal political viewpoints popular on TikTok. “Instead of suppressing speech on a single application, we could be addressing the root of the mental health crisis by targeting Big Tech’s pernicious, privacy-invasion business model of teenagers and children in our country,” Markey said.

TikTok has said the bill, if it becomes law, would infringe the free-speech rights of its 170 million U.S. users and “devastate” the estimated 7 million American businesses on the platform. It claims TikTok contributed $24 billion to the U.S. economy in 2023 .

The TikTok divest-or-ban legislation has been opposed by the ACLU and other advocacy groups.

“This is still nothing more than an unconstitutional ban in disguise,” Jenna Leventoff, senior policy counsel at the ACLU, said in a statement Tuesday prior to the Senate vote. “Banning a social media platform that hundreds of millions of Americans use to express themselves would have devastating consequences for all of our First Amendment rights, and will almost certainly be struck down in court.”

Because of its Chinese ties, TikTok has been a political football in the United States for years, as well as in other countries (including India, where it’s been banned since June 2020 ). TikTok has prevailed in challenging other laws in the U.S. seeking to ban the app. Last December, a federal judge blocked Montana’s first-of-its-kind statewide ban of TikTok , ruling that the law likely violated the First Amendment. An attempt by the Trump administration to force ByteDance to sell TikTok or face a ban also was found unconstitutional by federal courts on First Amendment grounds.

Backers of the TikTok bill argue that it doesn’t restrict free speech, saying it only requires apps to be owned by a company that isn’t subject to the control of an adversarial foreign government. As a precedent, the legislation’s proponents point to the 2020 sale of dating app Grindr by Chinese gaming company Beijing Kunlun Tech Co. to a group of U.S.-based investors, a transaction forced by the U.S. government over concerns about the privacy of the app’s users.

Per the text of the bill, legal challenges to the “Protecting Americans From Foreign Adversary Controlled Applications Act” may be filed only in the U.S. Court of Appeals for the District of Columbia Circuit.

If TikTok is unsuccessful in getting the divest-or-ban law overturned, it is unlikely that ByteDance would sell its ownership stake — and that the app would effectively become outlawed in the U.S. Chinese officials have said the government would “firmly oppose” any forced sale of TikTok, which would represent a technology export and be subject to the government’s approval. “You’re not going to be able to force ByteDance to divest,” James Lewis, SVP at the Center for Strategic and International Studies, told the New York Times last month.

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President Biden signs law to ban TikTok nationwide unless it is sold

Bobby Allyn

President Biden has signed a law that gives ByteDance up to a year to fully divest from TikTok, or face a nationwide ban. Kiichiro Sato/AP hide caption

President Biden has signed a law that gives ByteDance up to a year to fully divest from TikTok, or face a nationwide ban.

President Biden on Wednesday signed a law that would ban Chinese-owned TikTok unless it is sold within a year.

It is the most serious threat yet to the video-streaming app's future in the U.S., intensifying America's tech war with China.

Still, the law is not expected to cause any immediate disruption to TikTok, as a forthcoming legal challenge, and various hurdles to selling the app, will most likely cause months of delay.

The measure was tucked into a bill providing foreign aid for Israel, Ukraine and Taiwan. The law stipulates that ByteDance must sell its stake in TikTok in 12 months under the threat of being shut down.

U.S. bans noncompete agreements for nearly all jobs

The move is the culmination of Washington turning the screws on TikTok for years.

Chinese tech giant ByteDance, in 2017, purchased the popular karaoke app Musical.ly and relaunched the service as TikTok. Since then, the app has been under the microscope of national security officials in Washington fearing possible influence by the Chinese government.

Despite concerns in Washington, TikTok has soared. It has become the trendsetter in the world of short-form video and is used by 170 million Americans, which is about half of the country. It is where one-third of young people get their news, according to Pew Research Center.

Trump to score additional $1.2 billion windfall thanks to his Truth Social app

Yet lawmakers and the Biden administration argue that as long as TikTok is owned by a Chinese company, it is beholden to the dictates of China's authoritarian regime

"Congress is not acting to punish ByteDance, TikTok or any other individual company," said Democratic Sen. Maria Cantwell, who chairs the Senate Commerce Committee, in remarks on the Senate floor Tuesday afternoon.

"Congress is acting to prevent foreign adversaries from conducting espionage, surveillance, maligned operations, harming vulnerable Americans, our servicemen and women, and our U.S. government personnel."

In a video posted to the platform soon after Biden signed the bill, TikTok CEO Shou Zi Chew said he is confident TikTok would win in court, adding that users should not expect issues with the app in the meantime.

"Rest assured, we aren't going anywhere," Chew said. "The facts and the Constitution are on our side and we expect to prevail again."

Google worker says the company is 'silencing our voices' after dozens are fired

Tiktok plans to take biden administration to court over the law.

If not sold within a year, the law would make it illegal for web-hosting services to support TikTok, and it would force Google and Apple to remove TikTok from app stores — rendering the app unusable with time.

It marks the first time the U.S. has passed a law that could trigger the ban of a social media platform, something that has been condemned by civil liberties groups and constitutional scholars.

TikTok has vowed to take the Biden administration to court, claiming the law would suppress the free speech of millions of Americans.

The sentiment was echoed by Kate Ruane, who runs the Center for Democracy & Technology's Free Expression Project, who said the law is unconstitutional and a blow to free expression in the U.S.

"Congress shouldn't be in the business of banning platforms," Ruane said. "They should be working to enact comprehensive privacy legislation that protects our private data no matter where we choose to engage online."

Selling TikTok won't be so easy

Any company, or set of investors, angling to purchase TikTok would have to receive the blessing of the Chinese government, and officials in Beijing have strongly resisted a forced sell.

In particular, ByteDance owns the engine of TikTok, its hyper-personalized algorithm that pulls people in and keeps them highly engaged with their feed.

Chinese officials have placed content-recommendation algorithms on what is known as an export-control list, meaning the government has additional say over how the technology is ever sold.

Law took TikTok by surprise

By almost any measure, the law passed rapidly, and it caught many inside TikTok off guard, especially because the company had just breathed a sigh of relief.

Last month, the House passed a bill to compel TikTok to find a buyer, or face a nationwide ban, but the effort stalled in the Senate.

The legislation gave TikTok a six-month window to find a buyer, which some senators said was too little time.

A new push, this time attaching the divest-or-be-banned provision to foreign aid, fasted-tracked the proposal. It mirrors last month's attempt, but it extends the sell-by deadline, now giving TikTok nine months to find a buyer, with the option of a three-month extension if a potential acquisition is in play.

Sen. Markey: 'American companies are doing the same thing'

Lawmakers from both parties have argued that TikTok poses a national security risk to Americans, since the Chinese government could use the app to spy on Americans, or influence what U.S. users see on their TikTok feeds, something that has gained new urgency in an election year.

But some have pushed back, including Democratic Sen. Edward Markey of Massachusetts. He said on the Senate floor on Tuesday that there is "no credible evidence" that TikTok presents a real national security threat just because its parent company is based in China.

National intelligence laws in China would require ByteDance to hand over data on Americans if authorities there sought it, but TikTok says it has never received such a request.

Markey said concerns about digital security, the mental health of young people and data privacy should be addressed with comprehensive legislation encompassing the entire tech industry, not just TikTok.

"TikTok poses a serious risk to the privacy and mental health of our young people," Markey said. "But that problem isn't unique to TikTok and certainly doesn't justify a TikTok ban," he said. "American companies are doing the same thing, too."

Convert Tool(Text,Speech,Hex‪)‬ 4+

Text,speech,hex convert, sang hyeon kim, designed for iphone, iphone screenshots, description.

Conversion Utility is a versatile app designed to handle various conversion tasks. This app offers numeral system conversion, speech-to-text (STT), and text-to-speech (TTS) functionalities, enabling users to perform essential conversions efficiently. With a user-friendly interface, it is accessible to everyone and adapts flexibly to diverse conversion needs. Whether for daily tasks or professional demands, tackle all your conversion needs with this single app.

Version 1.1.2

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The developer, Sang Hyeon Kim , indicated that the app’s privacy practices may include handling of data as described below. For more information, see the developer’s privacy policy .

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The developer does not collect any data from this app.

Privacy practices may vary, for example, based on the features you use or your age. Learn More

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Congress Passed a Bill That Could Ban TikTok. Now Comes the Hard Part.

President Biden has signed the bill to force a sale of the video app or ban it. Now the law faces court challenges, a shortage of qualified buyers and Beijing’s hostility.

Share full article

A crowd of people, all holding signs that support TikTok.

By Sapna Maheshwari and David McCabe

Sapna Maheshwari reported from New York, and David McCabe from Washington.

A bill that would force a sale of TikTok by its Chinese owner, ByteDance — or ban it outright — was passed by the Senate on Tuesday and signed into law Wednesday by President Biden.

Now the process is likely to get even more complicated.

Congress passed the measure citing national security concerns because of TikTok’s Chinese ties. Both lawmakers and security experts have said there are risks that the Chinese government could lean on ByteDance for access to sensitive data belonging to its 170 million U.S. users or to spread propaganda.

The law would allow TikTok to continue to operate in the United States if ByteDance sold it within 270 days, or about nine months, a time frame that the president could extend to a year.

The measure is likely to face legal challenges, as well as possible resistance from Beijing, which could block the sale or export of the technology. It’s also unclear who has the resources to buy TikTok, since it will carry a hefty price tag.

The issue could take months or even years to settle, during which the app would probably continue to function for U.S. consumers.

“It’s going to be a royal mess,” said Anupam Chander, a visiting scholar at the Institute for Rebooting Social Media at Harvard and an expert on the global regulation of new technologies.

TikTok pledged to challenge the law. “Rest assured, we aren’t going anywhere,” its chief executive, Shou Chew, said in a video posted to the platform. “We are confident, and we will keep fighting for your rights in the courts.”

Here’s what to expect next.

TikTok’s Day in Court

TikTok is likely to start by challenging the measure in the courts.

“I think that’s the one certainty: There will be litigation,” said Jeff Kosseff, an associate professor of cybersecurity law at the Naval Academy.

TikTok’s case will probably lean on the First Amendment, legal experts said. The company is expected to argue that a forced sale could violate its users’ free speech rights because a new owner could change the app’s content policies and reshape what users are able to freely share on the platform.

“Thankfully, we have a Constitution in this country, and people’s First Amendment rights are very important,” Michael Beckerman, TikTok’s vice president of public policy, said in an interview with a creator on the platform last week. “We’ll continue to fight for you and all the other users on TikTok.”

Other groups, like the American Civil Liberties Union, which has been a vocal opponent of the bill, may also join the legal fight. A spokeswoman for the A.C.L.U. said on Tuesday that the group was still weighing its role in potential litigation challenging the law.

The government will probably need to make a strong case that ByteDance’s ownership of TikTok makes it necessary to limit speech because of national security concerns, the legal experts said.

TikTok already has a strong record in similar First Amendment battles. When he was president, Donald J. Trump tried to force a sale or ban of the app in 2020, but federal judges blocked the effort because it would have had the effect of shutting down a “platform for expressive activity.” Montana tried to ban TikTok in the state last year because of the app’s Chinese ownership, but a different federal judge ruled against the state law for similar reasons.

Only one narrower TikTok restriction has survived a court challenge. The governor of Texas announced a ban of the app on state government devices and networks in 2022 because of its Chinese ownership and related data privacy concerns. Professors at public universities challenged the ban in court last year, saying it blocked them from doing research on the app. A federal judge upheld the state ban in December, finding it was a “reasonable restriction” in light of Texas’ concerns and the narrow scope affecting only state employees.

Small Buyer Pool

Analysts estimate that the price for the U.S. portion of TikTok could be tens of billions of dollars.

ByteDance itself is one of the world’s most valuable start-ups , with an estimated worth of $225 billion, according to CB Insights, a firm that tracks venture capital and start-ups.

The steep price tag would limit the list of who could afford TikTok. Tech giants like Meta or Google would probably be blocked from an acquisition because of antitrust concerns.

Private equity firms or other investors could form a group to raise enough money to buy TikTok. Former Treasury Secretary Steven Mnuchin said in March that he wanted to build such a group. And anyone who can pony up the money still has to pass muster with the U.S. government, which needs to sign off on any purchase.

Few others have expressed public interest in buying the app.

The last time the government tried to force ByteDance to sell TikTok in 2020, the company held talks with Microsoft and the software company Oracle. (Oracle and Walmart ultimately appeared to reach an agreement with ByteDance, but the deal never materialized .)

A Complicated Divestment

Even if TikTok approaches a sale, the process of separating TikTok from ByteDance is likely to be messy.

The legislation prohibits any connection between ByteDance and TikTok after a sale. Yet TikTok employees use ByteDance software in their communications, and the company’s employees are global, with executives in Singapore, Dublin, Los Angeles and Mountain View, Calif.

It’s unclear if ByteDance would consider selling TikTok’s entire global footprint or just its U.S. operations, where the company has nearly 7,000 employees.

Breaking off just the U.S. portion of TikTok could prove particularly challenging. The app's recommendation algorithm, which figures out what users like and serves up content, is key to the success of the app. But Chinese engineers work on that algorithm, which ByteDance owns.

During Mr. Trump’s attempt to force a sale in 2020, the Chinese government issued export restrictions that appeared to require its regulators to grant permission before ByteDance algorithms could be sold or licensed to outsiders.

The uncertainty around the export of the algorithm and other ByteDance technology could also deter interested buyers.

China’s Unpredictable Role

The Chinese government could also try to block a TikTok sale.

Chinese officials criticized a similar bill after the House passed it in March, although they have not yet said whether they would block a divestment. About a year ago, China’s commerce ministry said it would “firmly oppose” a sale of the app by ByteDance.

Chinese export regulations appear to cover TikTok’s content recommendation algorithm, giving Beijing a say in whether ByteDance could sell or license the app’s most valuable feature.

It “is not a foregone conclusion by any means” that China will allow a sale, said Lindsay Gorman, a senior fellow at the German Marshall Fund who specializes in emerging tech and China.

China may retaliate against American companies. On Friday, China’s Cyberspace Administration asked Apple to remove Meta’s WhatsApp and Threads from its App Store, according to the iPhone manufacturer. The Chinese government cited national security reasons in making the demand.

Sapna Maheshwari reports on TikTok, technology and emerging media companies. She has been a business reporter for more than a decade. Contact her at [email protected] . More about Sapna Maheshwari

David McCabe covers tech policy. He joined The Times from Axios in 2019. More about David McCabe

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How to Convert Text to Speech on Linux: 12 Steps (with Pictures)

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COMMENTS

Top 10 Best Open Source Speech Recognition Tools for Linux
7. Mycroft. Mycroft comes with an easy-to-use open source voice assistant for converting voice to text. It is regarded as one of the most popular Linux speech recognition tools in modern time, written in Python. It allows users to make the best use of this tool in a science project or enterprise software application.
13 Best Free Linux Speech Recognition Tools
Deep-learning toolkit for training and deploying speech-to-text models. Kaldi. C++ toolkit designed for speech recognition researchers. SpeechBrain. All-in-one conversational AI toolkit based on PyTorch. ESPnet. End-to-End speech processing toolkit. deepspeech.pytorch. Implementation of DeepSpeech2 using Baidu Warp-CTC.
Top 11 Open Source Speech Recognition/Speech-to-Text Systems
4. Flashlight ASR (Formerly Wav2Letter++) If you are looking for something modern, then this one can be included. Flashlight ASR is an open source speech recognition software that was released by Facebook's AI Research Team. The code is a C++ code released under the MIT license.
How to enable speech-to-text in Linux with this simple app
Open your terminal window and install. Log into your desktop and open the terminal window app. Once the app is open, paste the following command and hit Enter on your keyboard: flatpak install ...
The Best Speech-to-Text Apps and Tools for Every Type of User
Dragon Professional. $699.00 at Nuance. See It. Dragon is one of the most sophisticated speech-to-text tools. You use it not only to type using your voice but also to operate your computer with ...
Speech to Text Transcription in Linux
Picovoice offers Leopard Speech-to-Text for batch transcription. It is remarkable because it processes voice data 100% on your device and hence is private by design (HIPAA and GDPR compliant). It also allows adding custom vocabulary and boosting specific phrases using the Picovoice Console.
Speech to Text Software for Linux
Speech to text software, sometimes known as dictation software, can be used on desktop machines, or speech to text apps can be used on a smartphone. Speech to text software and apps can be standalone products, or built into existing applications. Compare the best Speech to Text software for Linux currently available using the table below.
nerd-dictation: A fantastic Open Source speech to text software for
The steps to install are fairly simple and documented below for reference: nerd-dictation allows you to dictate text into any software or editor which is open so I can dictate into a word document or a blog post or even the command prompt. Previously I have used tried using software like otter.ai which actually works quite well but doesn't ...
GitHub
spchcat is a command-line tool that reads in audio from .WAV files, a microphone, or system audio inputs and converts any speech found into text. It runs locally on your machine, with no web API calls or network activity, and is open source. It is built on top of Coqui's speech to text library, TensorFlow, KenLM, and data from Mozilla's Common Voice project.
Ubuntu Speech-to-Text Tutorial
Picovoice Leopard Speech-to-Text processes voice locally on the device while matching the accuracy of API alternatives from Big Tech. Developers can start transcribing in seconds with Picovoice's Free Plan, even for commercial projects. Leopard comes with a total package size of 20MB (compared to GBs of FOSS alternatives).
Speech Note Transcribes Voice to Text on Linux
August 28, 2023. Speech Note is an offline, AI-powered app able to transcribe your speech into text in a variety of different languages. A reader got in touch to point me towards the app — thanks, David! — and given that it sounds pretty cool I figured I'd give it a spotlight on the site. Speech Note use OpenAI's Whisper and a stack of ...
Speech Note: Text to Speech, Speech to Text App for Linux
Speech Note: Features. Here are the key technologies which are working under the hood of this app. Speech to Text (STT): Harnessing the prowess of industry-leading STT engines like Coqui STT, Vosk, and whisper.cpp, Speech Note transforms spoken words into digital text with astonishing accuracy.Bid farewell to the tedious task of manual transcription, and say hello to a new era of efficiency.
GitHub
It uses Speech to Text, Text to Speech and Machine Translation to do so. Text and voice processing take place entirely offline, locally on your computer, without using a network connection. Your privacy is always respected. No data is sent to the Internet. Speech Note uses many different processing engines to do its job. Currently these are used:
Speech Note Transcribes Voice to Text on Linux
Speech Note is an offline, AI-powered app able to transcribe your speech into text in a variety of different languages. A reader got in touch to point me towards the... The post Speech Note Transcribes Voice to Text on Linux is from OMG! Linux and reproduction without permission is, like, a nope.
How to enable speech-to-text in Linux with this simple app
First, you'll need to download and install the app onto your Linux system. Don't worry, it's a breeze to install and won't take up much space on your hard drive. Once installed, simply ...
Install Speech Note on Linux
Speech Note let you take, read and translate notes in multiple languages. It uses Speech to Text, Text to Speech and Machine Translation to do so. Text and voice processing take place entirely offline, locally on your computer, without using a network connection. Your privacy is always respected.
eSpeak: Text To Speech Tool For Linux
eSpeak is a command line tool for Linux that converts text to speech. This compact speech synthesizer provides support for English and many other languages. It is written in C. eSpeak reads the text from the standard input or input file. The voice generated, however, is nowhere close to a human voice. But it is still a compact and handy tool if ...
Speech Recognition to Text in Linux, Ubuntu using Google Docs
There is not much speech recognition software available in Linux systems, including native desktop apps. There are some apps available that use IBM Watson and other APIs to convert speech to text, but they are not user-friendly and require an advanced level of user interactions, e.g. a little bit of programming or scripting in respective languages.
Speech to text online, Mac, Windows and Linux integration
Voice notebook. Voice notebook is a voice recognition application for converting speech to text (a good external microphone is strongly recommended). It can also convert an audio file to text. The current version works only for the Chrome browser in Windows, Mac and Linux OS (for Android and iOS users there are special Android, iOS applications).
Speech to Text Software Suite for Linux
The VoxSigma software suite for Linux offers large vocabulary speech-to-text capabilities in multiple languages. It includes adaptive features allowing the transcription of noisy speech, such as speech over background music. The software suite has been designed for professional users needing to transcribe large quantities of audio and video ...
An In-Depth Guide to Open Source Text-to-Speech Engines for Linux
It comes bundled with many Linux distributions due to being open source (GPLv3 license). The voices tend to sound robotic but the speech is clear and works well. To install on Debian/Ubuntu: $ sudo apt install espeak. On Fedora: $ sudo dnf install espeak. Arch Linux: $ sudo pacman -S espeak. Basic usage is simple.
Top Available
List of available suggestions for Linux you can find below. Save these options to have at hand when you will need transcription tools for Linux OS. 1. Transcriberry. This is one of the best voice-to-text software we recommend you assess in the first turn while making your choice.
Speech to text Linux apps? : r/linux
Welcome to /r/Linux! This is a community for sharing news about Linux, interesting developments and press. If you're looking for tech support, /r/Linux4Noobs is a friendly community that can help you. Please also check out: https://lemmy.ml/c/linux and Kbin.social/m/Linux Please refrain from posting help requests here, cheers.
How to use WhatsApp on your computer
2. On your Android phone, open WhatsApp, and then go to the three-dot menu (⋮) in the upper-right corner and select Linked devices.. 3. Tap the Link a device button, authenticate your identity ...
Scraibe
Meet Scraibe: The easiest way to turn Audio & Video files into Text! Direct File-to-Text Transcription Leverage the precision of OpenAI's Whisper and Apple's Neural Engine with Scraibe. Convert your audio and video files into readable text directly on your device or through our swift cloud-based service. Perfect for all your transcription needs.
Senate Passes TikTok Ban Bill, Setting Up First Amendment Battle
The U.S. Senate voted Tuesday to approve a bill that would ban TikTok nationwide unless Chinese parent company ByteDance sells its stake in the popular app. The development will likely result in a ...
The Best Text-to-Speech Apps and Tools for Every Type of User
The Best Operating Systems: Windows, macOS, Linux, or ChromeOS? All Operating Systems; ... The free app TTSMaker is the best text-to-speech app I can find for running in a browser. Just copy your ...
U.S. bans TikTok unless it is sold : NPR
President Biden on Wednesday signed a law that would ban Chinese-owned TikTok unless it is sold within a year. It is the most serious threat yet to the video-streaming app's future in the U.S ...
Convert Tool(Text,Speech,Hex‪)‬ 4+
Download Convert Tool(Text,Speech,Hex) and enjoy it on your iPhone, iPad, and iPod touch. ‎Conversion Utility is a versatile app designed to handle various conversion tasks. This app offers numeral system conversion, speech-to-text (STT), and text-to-speech (TTS) functionalities, enabling users to perform essential conversions efficiently.
Biden Signs TikTok Ban Bill Into Law. Here's What Happens Next.
The company is expected to argue that a forced sale could violate its users' free speech rights because a new owner could change the app's content policies and reshape what users are able to ...

Top 10 Best Open Source Speech Recognition Tools for Linux

Open Source Speech Recognition Tools

2. CMUSphinx

3. DeepSpeech

4. Wav2Letter++

8. OpenMindSpeech

9. SpeechControl

10. Deepspeech.pytorch

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Changes in version 4.4.0

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eSpeak: Text To Speech Tool For Linux

Install eSpeak

GUI Version: espeakedit

A New Tool: eSpeak NG

Wrapping Up

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Speech Recognition to Text in Linux, Ubuntu using Google Docs

How to convert speech to text

Step 1: Open Google Docs

Step 2: Launch Voice Typing

Step 3: Click on speak button

Step 4: Speak and record

Troubleshooting

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An In-Depth Guide to Open Source Text-to-Speech Engines for Linux

Introduction to Text-to-Speech

eSpeak – Lightweight Open Source TTS

Festival – Framework for Building TTS Voices

Pico TTS – Optimized Small Footprint Engine

gTTS – Leveraging Google‘s TTS API

Comparing Voice Quality Between TTS Engines

Additional Tips and Tricks

Leveraging TTS Engines in Shell Scripts

Appendix: Quick Reference of Engines

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