Open Source Linux Speech Software
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Speech Software for Linux
View 18 business solutionsBrowse free open source Speech software and projects for Linux below. Use the toggles on the left to filter open source Speech software by OS, license, language, programming language, and project status.
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Buzz
Transcribe and translate audio offline on your personal computer
Buzz transcribes and translates audio to text offline using OpenAI's Whisper. Import audio and video files into Buzz and export them as TXT, SRT, or VTT files. Buzz supports Whisper, Whisper.cpp, Faster Whisper, Whisper-compatible models from the Hugging Face repository, and the OpenAI Whisper API. Get linux versions from: - https://flathub.org/apps/io.github.chidiwilliams.Buzz - https://snapcraft.io/buzz Home page of Buzz https://github.com/chidiwilliams/buzz This is official installation distribution mirror for Buzz. Note for Windows: App is not signed, you will get a warning when you install it. Select More info -> Run anyway. -
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Text to Speech engine for English and many other languages. Compact size with clear but artificial pronunciation. Available as a command-line program with many options, a shared library for Linux, and a Windows SAPI5 version.
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eGuideDog project develops free software for the blind. Currently, we focus on WebSpeech, Ekho TTS and WebAnywhere.
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Open JTalk is a Japanese text-to-speech synthesis system. This software is released under the Modified BSD license.
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VCClient
Software that uses AI to perform real-time voice conversion
VCClient is a real-time voice conversion system that uses machine learning models to transform a speaker’s voice into another voice with minimal latency. It is designed for live applications such as streaming, gaming, and virtual communication, where immediate feedback is essential. The system supports multiple voice conversion models, including RVC and other neural network-based approaches, allowing users to switch between different voices or customize their output. It provides both a graphical user interface and API access, making it suitable for casual users as well as developers who want to integrate voice transformation into their own applications. The project also supports GPU acceleration, enabling faster inference and smoother real-time performance on compatible hardware. Additionally, it includes tools for training and managing voice models, giving users the ability to create personalized voice profiles. -
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RHVoice
Free open source speech synthesizer for Russian and other languages
RHVoice is a free and open-source multilingual speech synthesizer. Its developers hope to give more visually impaired people the ability to use a good free synthesis voice reading in their native language with their screen reader. We are especially interested in supporting those languages for which there are currently no good voices that could be used with a screen reader. The creator of RHVoice, Olga Yakovleva, is blind herself. Many of the contributors to the RHVoice project, both programmers and non-programmers, are blind or partially sighted. -
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MMDAgent is the toolkit for building voice interaction systems. Users can design users own dialog scenario, 3D agents, and voices. This software is released under the Modified BSD license.
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Sinsy
HMM-based singing voice synthesis system
Sinsy is an HMM-based singing voice synthesis system. This software is released under the Modified BSD license. -
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WaveSurfer is an open source tool for sound visualization and manipulation. Typical applications are speech/sound analysis and sound annotation/transcription. WaveSurfer may be extended by plug-ins as well as embedded in other applications.
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Mumble
Low-latency, high quality voice chat for gamers
Mumble is an open source, low-latency, high quality voice chat software primarily intended for use while gaming. It includes game linking, so voice from other players comes from the direction of their characters, and has echo cancellation so the sound from your loudspeakers won't be audible to other players. -
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hts_engine is software to synthesize speech waveform from HMMs trained by the HMM-based speech synthesis system (HTS). This software is released under the Modified BSD license.
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Praat
Doing Phonetics By Computer
Praat is a speech analysis application and source repository for doing phonetics by computer. It was created by Paul Boersma and David Weenink at the University of Amsterdam. The software lets researchers, linguists, clinicians, teachers, and students analyze, synthesize, manipulate, and annotate speech recordings. It supports acoustic inspection through waveforms, spectrograms, pitch tracks, formants, intensity, and related phonetic measurements. Praat also includes scripting tools for automating repetitive analysis, building custom workflows, and processing larger speech datasets. The project is especially useful for academic phonetics, speech science, language documentation, pronunciation research, and publication-quality speech visualization. -
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SpeechRecognition
Speech recognition module for Python
Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using pip install SpeechRecognition. The first software requirement is Python 2.6, 2.7, or Python 3.3+. This is required to use the library. PyAudio is required if and only if you want to use microphone input (Microphone). PyAudio version 0.2.11+ is required, as earlier versions have known memory management bugs when recording from microphones in certain situations. To hack on this library, first make sure you have all the requirements listed in the "Requirements" section. -
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NoiseGator (Noise Gate)
A simple noise gate app intended for use with VOIPs like Skype.
Ever wanted to cut out background noise when talking with others on Skype? Now it's possible! NoiseGator is a light-weight noise gate application that routes audio through an audio input to an audio output. In real-time the audio level is analysed and if the average level is higher than the threshold the audio bypasses as normal. However, if the average level goes below the threshold, the gate closes and the audio is cut. When used with a virtual audio cable it can act as a noise gate for a either a sound input(microphone) or sound output(speakers). Can also be used to gate noise from your own mic or play your microphone through your speakers. REQUIREMENTS: - Java 7 or higher for Windows. - Java 6 or higher for Mac. Java 7 recommended. - A virtual audio cable is required for use with VOIPs: For Windows users I recommend the VB-Cable driver (http://vb-audio.pagesperso-orange.fr/Cable/index.htm). Mac users can use SoundFlower. -
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Omilo - a text to speech application
Omilo is a simple text to speech application
Omilo is a simple text to speech application for Windows and Linux using Festival, Flite, Marytts and Piper voices. -
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SPTK is a suite of speech signal processing tools for UNIX environments, e.g., LPC analysis, PARCOR analysis, LSP analysis, PARCOR synthesis filter, LSP synthesis filter, vector quantization techniques, and other extended versions of them.
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TTS
Deep learning for text to speech
TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed, and quality. TTS comes with pre-trained models, tools for measuring dataset quality, and is already used in 20+ languages for products and research projects. Released models in PyTorch, Tensorflow and TFLite. Tools to curate Text2Speech datasets underdataset_analysis. Demo server for model testing. Notebooks for extensive model benchmarking. Modular (but not too much) code base enabling easy testing for new ideas. Text2Spec models (Tacotron, Tacotron2, Glow-TTS, SpeedySpeech). Speaker Encoder to compute speaker embeddings efficiently. Vocoder models (MelGAN, Multiband-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad, WaveRNN). If you are only interested in synthesizing speech with the released TTS models, installing from PyPI is the easiest option. -
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Coqui STT
The deep learning toolkit for speech-to-text
Coqui STT is a fast, open-source, multi-platform, deep-learning toolkit for training and deploying speech-to-text models. Coqui STT is battle-tested in both production and research. Multiple possible transcripts, each with an associated confidence score. Experience the immediacy of script-to-performance. With Coqui text-to-speech, production times go from months to minutes. With Coqui, the post is a pleasure. Effortlessly clone the voices of your talent and have the clone handle the problems in post. With Coqui, dubbing is a delight. Effortlessly clone the voice of your talent into another language and let the clone do the dub. With text-to-speech, experience the immediacy of script-to-performance. Cast from a wide selection of high-quality, directable, emotive voices or clone a voice to suit your needs. With Coqui text-to-speech, production times go from months to minutes. -
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annyang!
Speech recognition for your site
annyang is a tiny javascript library that lets your visitors control your site with voice commands. annyang supports multiple languages, has no dependencies, weighs just 2kb and is free to use. annyang understands commands with named variables, splats, and optional words. Use named variables for one word arguments in your command. Use splats to capture multi-word text at the end of your command (greedy). Use optional words or phrases to define a part of the command as optional. annyang plays nicely with all browsers, progressively enhancing browsers that support SpeechRecognition, while leaving users with older browsers unaffected. Grab the latest version of annyang.min.js, drop it in your html, and start adding commands. You can easily add a GUI for the user to interact with Speech Recognition using Speech KITT. Speech KITT is fully customizable and comes with many different themes, and instructions on how to create your own designs. -
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DeepSpeech
Open source embedded speech-to-text engine
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the instructions in the usage docs. If you want to use the pre-trained English model for performing speech-to-text, you can download it (along with other important inference material) from the DeepSpeech releases page. -
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PersonaPlex
PersonaPlex code
PersonaPlex is an open-source real-time conversational speech AI model that goes beyond traditional text chat by providing full-duplex speech-to-speech interaction, meaning it can listen and talk at the same time instead of waiting for you to finish speaking before responding. This architectural approach eliminates awkward pauses and makes conversations feel much more human-like, with natural behaviors such as overlapping speech, interruptions, and fluent turn-taking, traits that traditional AI assistants typically lack. PersonaPlex also supports persona and voice control, allowing developers to define the role and speaking style of the agent using text prompts and voice conditioning, making it suitable for applications like customized voice assistants, interactive character agents, or domain-specific conversational tools. Internally, it processes continuous audio streams in a hybrid input format so that speech understanding and generation occur jointly. -
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FreeTTS is a speech synthesis engine written entirely in the Java(tm) programming language. FreeTTS was written by the Sun Microsystems Laboratories Speech Team and is based on CMU's Flite engine. FreeTTS also includes a partial JSAPI 1.0
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Moonshine Voice
Fast and accurate automatic speech recognition (ASR) for edge devices
moonshine is an open-source automatic speech recognition toolkit optimized for fast and accurate transcription on edge devices and local environments. The project is designed to enable real-time voice applications such as live transcription, voice commands, and embedded speech interfaces without requiring heavy cloud infrastructure. Its architecture emphasizes low latency and flexible input handling, allowing audio streams of varying durations rather than relying on fixed processing windows. Moonshine supports multiple platforms including mobile, desktop, and embedded systems, and provides example projects to accelerate integration into real-world products. The toolkit also includes specialized model variants, including monolingual options that improve accuracy for specific languages. Overall, moonshine serves developers building privacy-conscious, on-device voice interfaces that demand high performance with minimal resource overhead. -
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MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.
