I Built a 1.6M-Parameter Offline Text-to-Speech Engine for Node.js — Here's How

The developer introduces TinyTTS, a text-to-speech project designed for low-resource environments. The primary goal was to create a TTS solution that's simple to use in Node.js, avoiding reliance on cloud services, Python, or large models. TinyTTS is built from scratch and uses a compact 1.6 million parameter model for efficient speech synthesis. It features an ~3.4MB ONNX model and offers high-quality 44.1 kHz output. The project achieves approximately 53x real-time performance on a laptop CPU, making it suitable for resource-constrained devices. TinyTTS boasts zero Python dependencies and provides a consistent output with its Python counterpart. The project is easily installed via npm and can be used with a simple API or CLI. The architecture involves text processing followed by phoneme generation, then utilizing the ONNX model to produce a WAV file. Compared to existing solutions, TinyTTS offers a balance of quality, size, and ease of use. The project is focusing on voice quality improvements, multi-language support, and expanding the voice library. Links to the npm, PyPI, GitHub, and a live demo are provided for users to explore the project further. The developer actively seeks feedback and edge case applications to improve the project's development.