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qwen-ttsQwen TTS 控制

Agent Skill

qwen-tts 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

541

周安装

23

GitHub Stars

公开资料未说明

下载量

190
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:qwen-tts(Qwen TTS 控制)
来源仓库:https://github.com/paki81/qwen-tts
仓库路径:skills/qwen-tts
安装命令:
npx skills add https://github.com/paki81/qwen-tts --skill qwen-tts
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/paki81/qwen-tts --skill qwen-tts

简介

qwen-tts 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • qwen-tts 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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:

SpeakerLanguageDescription
VivianChineseBright, slightly edgy young female
SerenaChineseWarm, gentle young female
Uncle_FuChineseSeasoned male, low mellow timbre
DylanChinese (Beijing)Youthful Beijing male, clear
EricChinese (Sichuan)Lively Chengdu male, husky
RyanEnglishDynamic male, rhythmic
AidenEnglishSunny American male
Ono_AnnaJapanesePlayful female, light nimble
SoheeKoreanWarm 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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.64%
按下载量换算66

Claude

28.8%
按下载量换算55

Cursor

21.96%
按下载量换算42

Gemini CLI

10.35%
按下载量换算20

安全审计

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可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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