Kokoro
Kokoro is an inference library for the Kokoro-82M text-to-speech model, an open-weight TTS model with 82 million parameters. It provides a simple pipeline for generating high-quality speech from text, designed for developers who need fast, cost-efficient TTS in production or personal projects.
✨ Key features
- Open-weight TTS model with 82 million parameters
- Apache-licensed weights for flexible deployment
- Supports multiple languages including English, Spanish, French, Hindi, Italian, Japanese, Portuguese, and Mandarin
- Simple KPipeline API for text-to-speech generation
- Outputs audio at 24kHz sample rate
- Can load custom voice tensors
🎯 Use cases
- Generate voiceovers for videos or podcasts
- Create audio versions of written content
- Build voice assistants or interactive applications
- Prototype TTS features in Colab notebooks
📦 Installation
🧰 Requirements: Python 3.9+ (recommended), espeak-ng installed for some languages, optional GPU acceleration on Apple Silicon with PYTORCH_ENABLE_MPS_FALLBACK=1.
pip install kokoro>=0.9.4 soundfile
For non-English languages, additional dependencies may be needed (e.g., pip install misaki[ja] for Japanese). On Windows, install espeak-ng from the official releases. On MacOS, set PYTORCH_ENABLE_MPS_FALLBACK=1 for GPU acceleration.
🚀 Usage
from kokoro import KPipeline
import soundfile as sf
pipeline = KPipeline(lang_code='a')
text = "Hello, world!"
generator = pipeline(text, voice='af_heart')
for i, (gs, ps, audio) in enumerate(generator):
sf.write(f'{i}.wav', audio, 24000)
❓ FAQ
What is Kokoro?
Kokoro is an open-weight TTS model with 82 million parameters, and this library provides inference for it.
How do I install kokoro?
You can install it via pip: pip install kokoro>=0.9.4 soundfile.
What languages are supported?
The README lists support for American English, British English, Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, and Mandarin Chinese.
Can I use a custom voice?
Yes, you can load a voice tensor directly and pass it to the pipeline as the voice argument.
📊 Repository
🤖 Overview, features, install steps and FAQ were generated from the project's README on Sep 4, 2026. Always check the original source before running commands.