hifi-gan
GAN vocoder that turns mel-spectrograms into high-fidelity speech audio, fast enough for real-time use.
fastrtc is an open-source audio project by gradio-app (gradio-app/fastrtc on GitHub). It has 4,631 GitHub stars and 436 forks, is released under the MIT license, and was last updated on GitHub on 12 January 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
The most-starred other Audio projects in the LibreAI catalogue — the realistic shortlist if fastrtc is not the right fit.
利用 AI 大模型和自动化工作流,根据主题或关键词一键生成高清短视频。Generate HD short videos from a topic or keyword with an automated AI workflow.
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++
Nearby Audio projects in the catalogue, closest in stars to fastrtc — keep exploring the shelf either side of it.
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
Free and open — grab the source, star the repo, and start creating.