tiny-tts

TinyTTS

Ultra-lightweight Text-to-Speech for Node.js — 1.6M params, 44.1kHz, ~53x real-time on CPU.

Pure Node.js offline TTS inference via ONNX Runtime. Zero Python dependency. The ONNX model (~6 MB) is auto-downloaded from HuggingFace on first use.

Installation

npm install tiny-tts

Quick Start

const TinyTTS = require('tiny-tts');

const tts = new TinyTTS();

// Synthesize and save to WAV
await tts.speak('Hello world!', { output: 'hello.wav' });

// With options
await tts.speak('This is a fast speech test.', {
  output: 'fast.wav',
  speaker: 'MALE',
  speed: 1.5
});

// Clean up
await tts.dispose();

CLI

# Basic usage
npx tiny-tts "Hello world!" -o hello.wav

# With options
npx tiny-tts "The weather is nice today." -o output.wav -s MALE --speed 1.2

Features

• Offline inference — no server, no API calls, no Python needed
• ONNX Runtime — fast CPU inference (~53x real-time)
• Neural G2P — ported g2p_en GRU model for accurate pronunciation of any English word
• Full CMU dictionary — 123,463 entries for precise phoneme lookup
• 100% G2P match with Python (PyPI) version across 542 test sentences
• Auto model download — ONNX model fetched from HuggingFace on first run

API

new TinyTTS(options?)

Option	Type	Default	Description
modelPath	string	(auto-download)	Path to ONNX model file

tts.speak(text, options?)

Option	Type	Default	Description
output	string	'output.wav'	Output WAV file path
speaker	string	'MALE'	Speaker ID (MALE or FEMALE)
speed	number	1.0	Speech speed (0.3–3.0)

Returns: Promise<Buffer> — WAV audio data (also saves to file if output is set)

tts.dispose()

Release ONNX session resources.

How It Works

• Text normalization — expands numbers, abbreviations, time expressions
• G2P pipeline — converts text to phonemes:
  • Apostrophe-aware word splitting (matches Python BERT tokenizer behavior)
  • CMU dictionary lookup (123K entries)
  • Neural G2P fallback (GRU encoder-decoder, identical to Python g2p_en)
• Phoneme → IDs — maps phonemes + tones to model input tensors
• ONNX inference — generates 44.1kHz audio waveform
• WAV output — saves as standard WAV file

Model Info

Metric	Value
Parameters	1.6M
Model size	~3.4 MB (ONNX FP16)
Sample rate	44.1 kHz
CPU speed	~53x real-time
Language	English

Python Version

Also available on PyPI with the same G2P output:

pip install tiny-tts

from tiny_tts import TinyTTS
tts = TinyTTS()
tts.speak("Hello world!", output_path="hello.wav")

License

Apache License 2.0

Links

• GitHub: github.com/tronghieuit/tiny-tts
• PyPI: pypi.org/project/tiny-tts
• npm: npmjs.com/package/tiny-tts
• Demo: huggingface.co/spaces/backtracking/tiny-tts-demo