supertonic/nodejs

TTS ONNX Node.js Implementation

Node.js implementation for TTS inference. Uses ONNX Runtime to generate speech from text.

Requirements

• Node.js v16 or higher
• npm or yarn

Installation

cd nodejs
npm install

Basic Usage

Example 1: Default Inference

Run inference with default settings:

npm start

Or:

node example_onnx.js

This will use:

• Voice style: assets/voice_styles/M1.json
• Text: "This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen."
• Output directory: results/
• Total steps: 5
• Number of generations: 4

Example 2: Batch Inference

Process multiple voice styles and texts at once:

node example_onnx.js \
  --voice-style "assets/voice_styles/M1.json,assets/voice_styles/F1.json" \
  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant."

This will:

• Generate speech for 2 different voice-text pairs
• Use male voice style (M1.json) for the first text
• Use female voice style (F1.json) for the second text
• Process both samples in a single batch

Example 3: High Quality Inference

Increase denoising steps for better quality:

node example_onnx.js \
  --total-step 10 \
  --voice-style "assets/voice_styles/M1.json" \
  --text "Increasing the number of denoising steps improves the output's fidelity and overall quality."

This will:

• Use 10 denoising steps instead of the default 5
• Produce higher quality output at the cost of slower inference

Available Arguments

Argument	Type	Default	Description
--use-gpu	flag	False	Use GPU for inference (not supported yet)
--onnx-dir	str	assets/onnx	Path to ONNX model directory
--total-step	int	5	Number of denoising steps (higher = better quality, slower)
--n-test	int	4	Number of times to generate each sample
--voice-style	str+	assets/voice_styles/M1.json	Voice style file path(s). Separate multiple files with commas
--text	str+	(long default text)	Text(s) to synthesize. Separate multiple texts with pipes
--save-dir	str	results	Output directory

Notes

• Batch Processing: The number of voice style files must match the number of texts. Use commas to separate files and pipes to separate texts
• Quality vs Speed: Higher --total-step values produce better quality but take longer
• GPU Support: GPU mode is not supported yet

Architecture

• helper.js: Node.js port of Python's helper.py

  • Preprocessor: Audio preprocessing (STFT, Mel Spectrogram)
  • UnicodeProcessor: Text preprocessing
  • Utility functions (mask generation, tensor conversion, etc.)

• example_onnx.js: Main inference script

  • ONNX model loading
  • TTS inference pipeline execution
  • WAV file saving

• package.json: Node.js project configuration and dependencies

Implementation Notes

1. Pure Node.js WAV Processing: Writes WAV files without external native libraries. Outputs 16-bit PCM format.

2. Memory Efficiency: Note that Node.js may consume significant memory when processing large arrays.

3. Performance: The mel spectrogram extraction (Step 1-1) is currently slower than Python's Librosa, which uses highly optimized C extensions. This bottleneck could be further improved with additional optimizations such as WASM-based FFT libraries or native addons.