According to AlphaMoat, as of 2026-09, Qwen3-tts has 4,960 downloads and 12 stars — ranked #1,860 of 5,078 AI skills overall, and #184 of 512 in Design & Media.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 151 | 4.4K | 9 | - |
| SkillHub ↗ | 486 | 5.0K | 12 | — |
Platforms count differently and update at different times.
The script supports language and speaker selection, instructions for emotion or speaking style, and WAV output. Initial setup installs dependencies and downloads the model; synthesis can then run offline on the local machine, with CPU or CUDA processing described in the documentation. Local files may contain private or project information; restrict access to the working directory and verify the selected files before processing.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 5.0K | — | 12 |
| 2026-08 | 4.4K | +3.4% | 12 |
| 2026-07 | 4.2K | — | 12 |
| 2026-05 | 3.9K | — | 12 |
| 2026-03 | 3.4K | — | 9 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: qwen-tts description: Local text-to-speech using Qwen3-TTS-12Hz-1.7B-CustomVoice. Use when generating audio from text, creating voice messages, or when TTS is requested. Supports 10 languages including Italian, 9 premium speaker voices, and instruction-based voice control (emotion, tone, style). Alternative to cloud-based TTS services like ElevenLabs. Runs entirely offline after initial model download. --- # Qwen TTS Local text-to-speech using Hugging Face's Qwen3-TTS-12Hz-1.7B-CustomVoice model. ## Quick Start
Generate speech from text: ```bash scripts/tts.py "Ciao, come va?" -l Italian -o output.wav ``` With voice instruction (emotion/style): ```bash scripts/tts.py "Sono felice!" -i "Parla con entusiasmo" -l Italian -o happy.wav ``` Different speaker: ```bash scripts/tts.py "Hello world" -s Ryan -l English -o hello.wav ``` ## Installation **First-time setup** (one-time): ```bash 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 ```bash 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:** ```bash scripts/tts.py "Benvenuto nel futuro del text-to-speech" -l Italian -o welcome.wav ``` **With emotion/instruction:** ```bash scripts/tts.py "Sono molto felice di vederti!" -i "Parla con entusiasmo e gioia" -l Italian -o happy.wav ``` **Different speaker:** ```bash scripts/tts.py "Hello, nice to meet you" -s Ryan -l English -o ryan.wav ``` **List available speakers:** ```bash 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: ```bash # 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:** ```bash # 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:** ```bash # 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)
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.