据 AlphaMoat 统计,截至 2026-09,Qwen3-tts 累计下载 4,960 次、获 12 个星标,在全部 5,078 个 AI 技能中排名第 1,860 位,在「设计创意」分类(512 个)中排名第 184 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 151 | 4,359 | 9 | - |
| SkillHub ↗ | 486 | 4,960 | 12 | — |
各平台的计数口径不同,统计时间不一致。
脚本支持选择语言与说话声音,通过指令控制情绪和表达风格,并输出 WAV 文件。首次需要安装依赖和下载模型,之后可在本机离线合成;文档描述了 CPU 或 CUDA 处理方式。 本地文件可能包含个人或项目资料;限制工作目录访问,并在处理前核对所选文件。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 4,960 | — | 12 |
| 2026-08 | 4,361 | +3.4% | 12 |
| 2026-07 | 4,218 | — | 12 |
| 2026-05 | 3,875 | — | 12 |
| 2026-03 | 3,442 | — | 9 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 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)
ContextWeave 架构图一键生成
用 Nano Banana Pro 生成或编辑图片的脚本技能。
用 whisper 命令行在本地把音频转写成文字或做翻译的技能。
通过 MCP 服务生成与编辑图表的技能。
面向界面设计的思路与落地建议技能,覆盖布局、交互流程、设计令牌与前端改动。
面向多家视频模型 API 的 AI 视频生成与编排技能。
用 ffmpeg 从视频里取出画面帧,或生成便于快速查看的缩略图。
用本地 Whisper 把音频文件转成文字,模型下载完成后可完全离线运行。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。