TTS ONNX Inference Examples

This guide provides examples for running TTS inference using Rust.

Installation

This project uses Cargo for package management.

Install Rust (if not already installed)

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Build the project

cargo build --release

Basic Usage

You can run the inference in two ways:

Using cargo run (builds if needed, then runs)
Direct binary execution (faster if already built)

Example 1: Default Inference

Run inference with default settings:

# Using cargo run
cargo run --release --bin example_onnx

# Or directly execute the built binary (faster)
./target/release/example_onnx

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:

# Using cargo run
cargo run --release --bin example_onnx -- \
  --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."

# Or using the binary directly
./target/release/example_onnx \
  --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 (M1.json) for the first text
Use female voice (F1.json) for the second text
Process both samples in a single batch

Example 3: High Quality Inference

Increase denoising steps for better quality:

# Using cargo run
cargo run --release --bin example_onnx -- \
  --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."

# Or using the binary directly
./target/release/example_onnx \
  --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 (default: CPU)
`--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)
`--text`	str+	(long default text)	Text(s) to synthesize
`--save-dir`	str	`results`	Output directory

Notes

Batch Processing: The number of --voice-style files must match the number of --text entries
Quality vs Speed: Higher --total-step values produce better quality but take longer
GPU Support: GPU mode is not supported yet
Known Issues: On some platforms (especially macOS), there might be a mutex cleanup warning during exit. This is a known ONNX Runtime issue and doesn't affect functionality. The implementation uses libc::_exit() and mem::forget() to bypass this issue.