Pocket TTS
A lightweight text-to-speech (TTS) application designed to run efficiently on CPUs. Forget about the hassle of using GPUs and web APIs serving TTS models. With Kyutai's Pocket TTS, generating audio is just a pip install and a function call away.
Supports Python 3.10, 3.11, 3.12, 3.13 and 3.14. Requires PyTorch 2.5+. Does not require the gpu version of PyTorch.
🔊 Demo | 🐱💻GitHub Repository | 🤗 Hugging Face Model Card | ⚙️ Tech report | 📄 Paper | 📚 Documentation
Main takeaways
- Runs on CPU
- Small model size, 100M parameters
- Audio streaming
- Low latency, ~200ms to get the first audio chunk
- Faster than real-time, ~6x real-time on a CPU of MacBook Air M4
- Uses only 2 CPU cores
- Python API and CLI
- Voice cloning
- Multi-language support: english, french, german, portuguese, italian, spanish
- Can handle infinitely long text inputs
- Can run on client-side in the browser
Additional languages may be added in the future.
Trying it from the website, without installing anything
Navigate to the Kyutai website to try it out directly in your browser. You can input text, select different voices, and generate speech without any installation.
Trying it with the CLI
The generate command
You can use pocket-tts directly from the command line. We recommend using
uv as it installs any dependencies on the fly in an isolated environment (uv installation instructions here).
You can also use pip install pocket-tts to install it manually.
This will generate a wav file ./tts_output.wav saying the default text with the default voice, and display some speed statistics.
uvx pocket-tts generate
# or if you installed it manually with pip:
pocket-tts generate
Modify the voice with --voice and the text with --text. We provide a small catalog of voices.
Choose a pretrained language model with --language when running generate, export-voice, or serve (default: english). Non-english languages have also biggers 24 layers variants that are higher quality but slower. You can select them by using for example --language italian_24l.
The --config option accepts only a local YAML path for custom weights.
You can take a look at this page which details the licenses for each voice.