Audio
hifi-gan
GAN vocoder that turns mel-spectrograms into high-fidelity speech audio, fast enough for real-time use.
★ 2,4 k étoilesMIT
Voir le guide →fastrtc est un projet de audio open source, créé par gradio-app (gradio-app/fastrtc sur GitHub). Il compte 4 631 étoiles sur GitHub et 436 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 12 janvier 2026.
FastRTC turns any Python function into a real-time audio or video stream over WebRTC or WebSockets
Write a Python generator that takes audio (or video) frames and yields responses.
Install from PyPI, adding the vad/tts extras if you want pause detection and text-to-speech.
Create a Stream with ReplyOnPause for audio conversations, and pick a delivery mode: built-in UI, FastAPI mount, or a phone number.
Start the stream and speak to your function in real time.
Built-in voice activity detection (the ReplyOnPause handler) runs your function when the user stops speaking.
Stream real-time audio or video over either transport, in send, receive, or send-receive modes.
Every stream can launch with a test interface via stream.ui.launch().
Mount a stream into an existing FastAPI application with stream.mount(app).
Get a temporary phone number to call your stream, using a Hugging Face token.
Optional vad and tts extras add pause detection and text-to-speech support.
Clone the project and enter its directory (library users can install from PyPI instead).
git clone https://github.com/gradio-app/fastrtc.git
cd fastrtcInstall the package, with the speech extras if you need them.
pip install fastrtc
pip install "fastrtc[vad, tts]"Wrap a reply function in a Stream and launch the built-in UI.
from fastrtc import Stream, ReplyOnPause
stream = Stream(handler=ReplyOnPause(fn), modality="audio", mode="send-receive")
stream.ui.launch()The Gradio team (gradio-app) — the same group behind the Gradio ML interface library.
Yes, it is MIT-licensed open source. FastPhone numbers are provided through Hugging Face and require an HF token.
No — the library is self-contained; you supply your own speech/LLM models inside your handler function.
FastRTC abstracts the transport and adds the conversational layer — VAD, turn-taking, a test UI, and FastAPI mounting — so you write a plain function instead of managing peers and tracks.
`pip install fastrtc`, wrap your function with `Stream(handler=ReplyOnPause(fn), ...)`, and call `stream.ui.launch()`.
GAN vocoder that turns mel-spectrograms into high-fidelity speech audio, fast enough for real-time use.
MCP server that turns any video — YouTube.
gTTS — Python library and CLI that turns text into spoken mp3 via Google Translate's speech API
Clone a voice from 5 seconds of audio and generate arbitrary speech in real time
Vietnamese TTS with instant voice cloning — on-device, real-time CPU inference, 48 kHz audio
Python library for audio and music analysis
Les autres projets de la catégorie Audio avec le plus d'étoiles du catalogue LibreAI — la sélection réaliste d'alternatives si fastrtc ne vous convient pas.
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Robust Speech Recognition via Large-Scale Weak Supervision
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
Clone a voice from 5 seconds of audio and generate arbitrary speech in real time
Port of OpenAI's Whisper model in C/C++
Projets de la catégorie Audio proches dans le catalogue, les plus proches en étoiles de fastrtc — continuez à explorer de part et d'autre.
Turn the beloved Kokoro voice model into an OpenAI-compatible speech API with one Docker command.
MOSS-TTS-Nano: a 0.1B open multilingual speech model that clones voices and streams in real time on CPU
Open-source AI video localization and dubbing for YouTube/Bilibili: speech recognition, subtitle translation, voice cloning, audio mixing and rendering. 开源 A…
WhisperLive: a nearly-live OpenAI Whisper transcription server for files, mics, and streams
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
MetaVoice-1B: a 1.2B-parameter foundation model for emotional, zero-shot text-to-speech
Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.