Open Source Speech Software
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Speech Software
View 4791 business solutionsBrowse free open source Speech software and projects 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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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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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 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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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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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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eGuideDog project develops free software for the blind. Currently, we focus on WebSpeech, Ekho TTS and WebAnywhere.
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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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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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Open JTalk is a Japanese text-to-speech synthesis system. This software is released under the Modified BSD license.
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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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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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Simple TTS Reader
A small clipboard reader
Simple TTS Reader is a small utility that reads text from your clipboard using Microsoft Speech API. Whenever you copy any text, the app instantly converts it into spoken words. Select your preferred speech engine from those installed on your system, such as Microsoft Zira, and adjust speed and volume for personalized playback. The application can also be minimized to the system tray. Plus, it is free and comes with an intuitive interface that makes it accessible to everyone. -
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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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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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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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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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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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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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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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Unofficial fork of the GyachE (www.phrozensmoke.com), intended for bug-fixes and further development.
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Voxal voice changer
Transform your voice in real-time voxal voice changer
Voxal Voice Changer is a program that allows you to modify your voice by applying various effects (e.g. pitch change, echo, etc.) in real-time. Effects can be added in any sequence and in any combination, allowing you to distort your voice beyond recognition. Take your audio to the next level! Our powerful Voice Changer software lets you morph your voice in real-time with stunning AI-powered quality. Whether you're looking to have fun, protect your privacy, or create engaging content, we have the perfect voice for you. Audio can be captured from various sources, pre-listening is available, and the most popular audio formats are supported. -
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Moshi
A speech-text foundation model for real time dialogue
Moshi is a speech-text foundation model and full-duplex spoken dialogue framework. It uses Mimi, a state-of-the-art streaming neural audio codec. Mimi processes 24 kHz audio, down to a 12.5 Hz representation with a bandwidth of 1.1 kbps, in a fully streaming manner (latency of 80ms, the frame size), yet performs better than existing, non-streaming, codecs like SpeechTokenizer (50 Hz, 4kbps), or SemantiCodec (50 Hz, 1.3kbps). Moshi models two streams of audio: one corresponds to Moshi, and the other one to the user. At inference, the stream from the user is taken from the audio input, and the one for Moshi is sampled from the model's output. Along these two audio streams, Moshi predicts text tokens corresponding to its own speech, its inner monologue, which greatly improves the quality of its generation. A small Depth Transformer models inter codebook dependencies for a given time step, while a large, 7B parameter Temporal Transformer models the temporal dependencies. -
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XZVoice
Free and open source text-to-speech software
Text-to-speech software developed by Electron + vue + ElementUI + js. The high-fidelity and flexible configuration of speech synthesis products opens up the closed loop of human-computer interaction and enables applications to sound realistically. A variety of timbres are available, and functions such as adjusting speech rate, intonation, and volume are provided. Technically, multi-level rhythmic pauses are taken into account to achieve the purpose of natural synthesizing rhythm, and comprehensively use acoustic parameters and linguistic parameters to establish multiple automatic prediction models based on deep learning. Using massive audio data to train the pronunciation model, the synthetic sound is real, full, cadenced, and expressive, and the MOS score has reached the professional level in the industry. -
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The Open VXI VoiceXML interpreter is a portable open source library that interprets the VoiceXML dialog markup language. It is designed to serve as a reference for parties interested in understanding how VoiceXML markup might be executed.
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Wrapper for vendors to simplify usage of the Java Speech API (JSR 113). Note that the spec is an untested early access and that there may be changes in the API.
