Overview
- Skill Key
- damiencronw/video-stt
- Author
- damiencronw
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/damiencronw/video-stt
- Latest Commit SHA
- 287ac8389e03dbb4a25f68a1e81558d742bae323
Extract audio from video URLs and transcribe using STT (Speech-to-Text). Supports local Whisper or cloud APIs. Use when: user provides a video URL and wants to know what is being said, transcribing YouTube videos, podcasts, or any video with audio.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 video-stt 技能。 若已安装,则直接安装 video-stt 技能。
# Video STT Skill 从视频 URL 提取音频并转换为文字 (Speech-to-Text) ## 环境要求 - **yt-dlp** - 下载视频/音频 - **ffmpeg** - 提取音频 - **Python** - 使用 uv 虚拟环境 ## 快速开始 ```bash # 进入脚本目录 cd ~/.openclaw/workspace/skills/video-stt/scripts # 运行转录 bash stt.sh "视频URL" ``` ## 使用方法 ```bash # 基本用法 bash stt.sh "https://youtube.com/watch?v=xxx" # 指定输出文件 bash stt.sh "https://youtube.com/watch?v=xxx" -o output.txt # 使用本地 Whisper 模型 bash stt.sh "https://youtube.com/watch?v=xxx" --local # 使用云端 API bash stt.sh "https://youtube.com/watch?v=xxx" --api openai ``` ## 支持的模型 ### 本地 (免费) - tiny - 最快,质量一般 - base - 平衡 - small - 较好 - medium - 很好 - large - 最佳(需要更多内存) ### 云端 API - OpenAI Whisper API - Azure Speech - Google Speech ## 输出格式 默认输出纯文本,可选: - `.txt` - 纯文本 - `.srt` - 字幕格式 - `.vtt` - WebVTT 字幕 - `.json` - 带时间戳的 JSON ## 环境变量 ```bash # OpenAI (如果使用云端) export OPENAI_API_KEY="sk-xxx" # 或者使用硅基流动 (更便宜) export SILICONFLOW_API_KEY="xxx" ``` ## 示例 ```bash # 转录 YouTube 视频 bash stt.sh "https://www.youtube.com/watch?v=dQw4w9WgXcQ" # 指定模型 bash stt.sh "https://youtube.com/watch?v=xxx" --model medium # 保存为 SRT bash stt.sh "https://youtube.com/watch?v=xxx" --format srt ``` ## Python 依赖 使用 uv 管理 Python 环境: ```bash # 创建虚拟环境 uv venv uv pip install yt-dlp whisper ffmpeg-python # 运行 uv run python stt.py "视频URL" ```
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