Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
F5 TTS is an open-source audio project by SWivid (SWivid/F5-TTS on GitHub). It has 15,330 GitHub stars and 2,240 forks, is released under the MIT license, and was last updated on GitHub on 21 September 2026.
Official code for "F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching"
Speech-to-text, text-to-speech, voice cloning, or music/SFX generation — each project here has a lane.
Python packages, Docker images, and C++ builds cover servers, desktops, and edge devices.
Download the weights or pick a voice; many tools bundle a strong default so you can start immediately.
Transcribe files, synthesize scripts, or generate music — then export standard audio formats.
Open speech recognition now rivals paid APIs on accuracy across languages.
Modern TTS is strikingly human — good enough for narration and voiceovers.
Clone a voice from a short sample for consistent characters and branding.
Compose backing tracks and sound effects from text descriptions.
Entire pipelines work without internet — ideal for private or field use.
Drop-in endpoints that mimic commercial APIs, so existing apps switch easily.
Download the source and move into the project folder.
git clone https://github.com/SWivid/F5-TTS.git
cd F5-TTSIsolate dependencies so nothing clashes with your other projects.
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activateInstall the requirements, then follow the README's launch command (it varies per project).
pip install -r requirements.txtExcellent — the leading open models match commercial services on clean audio, in many languages.
The tech clones from short samples; only ever clone voices you own or have explicit permission to use.
It is an open-source project at SWivid/F5-TTS with 2,240 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Transcription and TTS run on CPU acceptably; GPUs speed up batch jobs and music generation a lot.
Coverage varies — transcription is broadest, TTS quality is best in major languages.
Usually yes, but check both the code license and the model license.
Robust Speech Recognition via Large-Scale Weak Supervision
Port of OpenAI's Whisper model in C/C++
Faster Whisper transcription with CTranslate2
IndexTTS: industrial-level, controllable zero-shot text-to-speech with voice cloning
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text…
MOSS-TTS-Nano: a 0.1B open multilingual speech model that clones voices and streams in real time on CPU
The most-starred other Audio projects in the LibreAI catalogue — the realistic shortlist if F5 TTS 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 F5 TTS — keep exploring the shelf either side of it.
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Alibaba's open voice models: expressive, streaming-capable speech with free-form voice design.
Audio Editor
Gradio WebUI for creators and developers, featuring key TTS (Edge-TTS, kokoro) and zero-shot Voice Cloning (E2 & F5-TTS, CosyVoice), with Whisper audio proce…
Free and open — grab the source, star the repo, and start creating.