scripts/tts.py "Hello world" -s Ryan -l English -o hello.wav

Installation

First-time setup (one-time):

cd skills/public/qwen-tts
bash scripts/setup.sh

This creates a local virtual environment and installs qwen-tts package (~500MB).

Note: First synthesis downloads ~1.7GB model from Hugging Face automatically.

Usage

scripts/tts.py [options] "Text to speak"

Options

-o, --output PATH - Output file path (default: qwen_output.wav)
-s, --speaker NAME - Speaker voice (default: Vivian)
-l, --language LANG - Language (default: Auto)
-i, --instruct TEXT - Voice instruction (emotion, style, tone)
--list-speakers - Show available speakers
--model NAME - Model name (default: CustomVoice 1.7B)

Examples

Basic Italian speech:

scripts/tts.py "Benvenuto nel futuro del text-to-speech" -l Italian -o welcome.wav

With emotion/instruction:

scripts/tts.py "Sono molto felice di vederti!" -i "Parla con entusiasmo e gioia" -l Italian -o happy.wav

Different speaker:

scripts/tts.py "Hello, nice to meet you" -s Ryan -l English -o ryan.wav

List available speakers:

scripts/tts.py --list-speakers

Available Speakers

The CustomVoice model includes 9 premium voices:

Speaker	Language	Description
Vivian	Chinese	Bright, slightly edgy young female
Serena	Chinese	Warm, gentle young female
Uncle_Fu	Chinese	Seasoned male, low mellow timbre
Dylan	Chinese (Beijing)	Youthful Beijing male, clear
Eric	Chinese (Sichuan)	Lively Chengdu male, husky
Ryan	English	Dynamic male, rhythmic
Aiden	English	Sunny American male
Ono_Anna	Japanese	Playful female, light nimble
Sohee	Korean	Warm female, rich emotion

Recommendation: Use each speaker's native language for best quality, though all speakers support all 10 languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian).

Voice Instructions

Use -i, --instruct to control emotion, tone, and style:

Italian examples:

"Parla con entusiasmo"
"Tono serio e professionale"
"Voce calma e rilassante"
"Leggi come un narratore"

English examples:

"Speak with excitement"
"Very happy and energetic"
"Calm and soothing voice"
"Read like a narrator"

Integration with OpenClaw

The script outputs the audio file path to stdout (last line), making it compatible with OpenClaw's TTS workflow:

# OpenClaw captures the output path
cd skills/public/qwen-tts
OUTPUT=$(scripts/tts.py "Ciao" -s Vivian -l Italian -o /tmp/audio.wav 2>/dev/null)
# OUTPUT = /tmp/audio.wav

Performance

GPU (CUDA): ~1-3 seconds for short phrases
CPU: ~10-30 seconds for short phrases
Model size: ~1.7GB (auto-downloads on first run)
Venv size: ~500MB (installed dependencies)

Troubleshooting

Setup fails:

# Ensure Python 3.10-3.12 is available
python3.12 --version

# Re-run setup
cd skills/public/qwen-tts
rm -rf venv
bash scripts/setup.sh

Model download slow/fails:

# Use mirror (China mainland)
export HF_ENDPOINT=https://hf-mirror.com
scripts/tts.py "Test" -o test.wav

Out of memory (GPU): The model automatically falls back to CPU if GPU memory insufficient.

Audio quality issues:

Try different speaker: --list-speakers
Add instruction: -i "Speak clearly and slowly"
Check language matches text: -l Italian for Italian text

Model Details

Model: Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
Source: Hugging Face (https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice)
License: Check model card for current license terms
Sample Rate: 16kHz
Output Format: WAV (uncompressed)

qwen-tts

Qwen TTS

Quick Start