Kokoro TTS is a command-line interface (CLI) tool that provides text-to-speech (TTS) capabilities using the Kokoro model. It is designed for users who need to convert text from various formats into natural-sounding speech directly from their terminal, offering features like multi-language support, voice blending, and processing of EPUB and PDF documents.

How It Works

Kokoro TTS leverages the Kokoro-ONNX model for speech synthesis. It processes input text from files (TXT, EPUB, PDF) or standard input, allowing for flexible integration into existing workflows. Key features include voice blending with customizable weights, enabling users to create unique vocal characteristics by mixing different voices. The tool also supports splitting output into chapters for organized audio files and offers streaming playback for immediate audio feedback.

Quick Start & Requirements

• Installation: Recommended method is via PyPI: uv tool install kokoro-tts or pip install kokoro-tts. Alternatively, install from Git or clone and install locally.
• Prerequisites: Python 3.9-3.12.
• Model Files: Requires downloading voices-v1.0.bin and kokoro-v1.0.onnx to the working directory.
• Documentation: Usage examples and feature details are available in the README.

Highlighted Details

• Supports EPUB and PDF input, automatically extracting chapters and preserving structure.
• Offers voice blending with customizable weights (e.g., "voice1:60,voice2:40").
• Provides streaming audio playback and the ability to split output into separate chapter files.
• Supports both WAV and MP3 audio formats.

Maintenance & Community

This is a personal project, and contributions via Pull Requests are welcome.

Licensing & Compatibility

• License: MIT License.
• Compatibility: Permissive license suitable for commercial use and integration with closed-source projects.

Limitations & Caveats

Python 3.13+ is not currently supported. The project is described as a personal project, which may imply a smaller support or development community compared to larger, institutionally backed projects.