Audio
bark
Suno's text-prompted generative audio model: speech, music and sound effects from text prompts
★ 39,3 Tsd. SterneMIT
Anleitung ansehen →ChatTTS ist ein Open-Source-Projekt aus der Kategorie Audio von 2noise (2noise/ChatTTS auf GitHub). Es hat 39.892 Sterne auf GitHub und 4.257 Forks, wird unter der Lizenz AGPL-3.0 veröffentlicht und wurde zuletzt am 10. April 2026 auf GitHub aktualisiert.
A generative speech model built for daily dialogue — natural, conversational text-to-speech
Decide what you want from ChatTTS and check the README and requirements to confirm it fits your setup and Python environment.
Clone the repository from GitHub (github.com/2noise/ChatTTS) or use the documented install channel if you do not need the source.
Follow the README quickstart to install dependencies and set any required configuration or credentials.
Work through the README's first example end to end, then adapt it to your own project or data.
A generative speech model designed specifically for daily dialogue rather than narration.
Supports Chinese and English conversational speech.
Targets natural conversational delivery for LLM chat applications.
Installable from PyPI as ChatTTS, or from source.
Documents optional vLLM-based serving for faster inference.
Model and dataset details are documented in the README.
Start by getting the source and entering the project directory.
git clone https://github.com/2noise/ChatTTS.git
cd ChatTTSClone the repo and install the Python requirements.
git clone https://github.com/2noise/ChatTTS.git
cd ChatTTS
pip install -r requirements.txtInstall ChatTTS directly from PyPI for library use.
pip install ChatTTSIt is maintained by 2noise and contributors on GitHub, where the repository github.com/2noise/ChatTTS is the canonical home for code, issues and releases.
Yes — it is open source under the AGPL-3.0 license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.
No. It runs locally; note the code is AGPL-3.0 while model weights carry their own terms in the README.
Compared with Coqui TTS: ChatTTS is specialised for conversational dialogue prosody, while Coqui TTS is a general trainable TTS toolkit.
Clone github.com/2noise/ChatTTS, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.
Suno's text-prompted generative audio model: speech, music and sound effects from text prompts
MetaVoice-1B: a 1.2B-parameter foundation model for emotional, zero-shot text-to-speech
A speech-to-text server framework built on next-generation Kaldi.
Turn books and documents into natural speech with the Kokoro TTS model.
VITS — the original end-to-end text-to-speech model: a conditional VAE with adversarial learning, in PyTorch.
Private cross-platform speech-to-text with LLM cleanup built in.
Die anderen Projekte der Kategorie Audio mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls ChatTTS 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 ChatTTS bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Deep learning toolkit for text-to-speech, battle-tested in research and production
Suno's text-prompted generative audio model: speech, music and sound effects from text prompts
VoiceStudio is the open-source, fully-local ElevenLabs alternative — voice cloning, voice design, video dubbing, dictation, transcription & audiobook creatio…
Easily train a good VC model with voice data <= 10 mins!
Port of OpenAI's Whisper model in C/C++
VoxCPM2: tokenizer-free TTS for multilingual speech, creative voice design and true-to-life cloning
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.