Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Communication & Collaboration
Qwen3-tts
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.
skill openclawclawhub Free
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.
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- MAC_SERVER.md, README.md, SKILL.md, VOICEDESIGN.md, scripts/server.py, scripts/setup.sh
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- paki81
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Qwen TTS
Local text-to-speech using Hugging Face's Qwen3-TTS-12Hz-1.7B-CustomVoice model.
Quick Start
Generate speech from text: scripts/tts.py "Ciao, come va?" -l Italian -o output.wav With voice instruction (emotion/style): scripts/tts.py "Sono felice!" -i "Parla con entusiasmo" -l Italian -o happy.wav Different speaker: 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: SpeakerLanguageDescriptionVivianChineseBright, slightly edgy young femaleSerenaChineseWarm, gentle young femaleUncle_FuChineseSeasoned male, low mellow timbreDylanChinese (Beijing)Youthful Beijing male, clearEricChinese (Sichuan)Lively Chengdu male, huskyRyanEnglishDynamic male, rhythmicAidenEnglishSunny American maleOno_AnnaJapanesePlayful female, light nimbleSoheeKoreanWarm 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)
Category context
Messaging, meetings, inboxes, CRM, and teammate communication surfaces.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Docs2 Scripts
- SKILL.md
- MAC_SERVER.md
- README.md
- VOICEDESIGN.md
- scripts/server.py
- scripts/setup.sh