Background
In multi-language scenarios, traditional TTS systems often require complex dependency libraries and huge model files, leading to inefficient deployment. kokoro-ONNX solves this pain point with the optimized architecture of ONNX runtime.
Core Solutions
- Lightweight installation: Use
pip install -U kokoro-onnxOne-step installation of core components (~300MB), only 80MB for the quantized version - modular language pack: By
voices.jsonMulti-language configuration for document management, just replace the corresponding voice model to switch languages - Pre-compiled dependencies: ONNX runtime's cross-platform feature avoids environment compilation and supports macOS M1 natively.
- Quick Start Program: sequential implementation
uv init→uv add→ Download the model in three steps to complete the deployment
Implementation of recommendations
For high-frequency language switching scenarios, it is recommended to create a language model catalog structure, for example:/models/en/,/models/ja/The script automatically loads the corresponding paths of the.onnxDocumentation.
This answer comes from the articleKokoro-ONNX: Efficient Text-to-Speech Tool with Multi-Language and Multi-Voice SupportThe
May not be reproduced without permission:AI productivity tools " How to solve the rapid deployment challenge of multilingual text-to-speech?
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