Audio
Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
★ 109,9 Tsd. SterneMIT
Anleitung ansehen →F5 TTS ist ein Open-Source-Projekt aus der Kategorie Audio von SWivid (SWivid/F5-TTS auf GitHub). Es hat 15.330 Sterne auf GitHub und 2.240 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 21. September 2026 auf GitHub aktualisiert.
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
Die anderen Projekte der Kategorie Audio mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls F5 TTS nicht das Richtige ist.
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++
Verwandte Projekte der Kategorie Audio im Katalog, die F5 TTS bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
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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…
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.