Audio local

Skill jk241282/-deepseek-skills/audio-local

当用户发送音频文件或要求语音转文字、音频转录、录音识别时使用此 skill。使用本地 faster-whisper large-v3-turbo 进行语音识别。转录完成后，由 Claude 直接对文本进行总结、分析、翻译等后续处理。触发场景：用户上传音频/录音、要求语音转文字、会议转录、提取音频内容等。From its SKILL.md

Install

npx -y skills add jk241282/-deepseek-skills --skill audio-local

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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SKILL.md

1.5 KB, 411 tokens by cl100k_base, as published. Nobody here has run it

本地语音转文字

管线

音频 → faster-whisper(转录) → 原文 → Claude 后续处理

转录由本地模型完成，文字结果的总结/分析/翻译由 Claude 直接处理，无需再调 Ollama。

执行步骤

1. 确认音频路径

获取音频文件绝对路径。支持格式：mp3, wav, m4a, ogg, flac, webm。

2. 执行转录

python "<skill目录>/scripts/transcribe.py" "<音频路径>" <语言>

语言默认 zh，英文音频用 en
模型路径可通过环境变量 WHISPER_MODEL_PATH 设置，默认为 ~/models/faster-whisper-large-v3-turbo
输出纯文本原文

3. 后续处理

拿到转录原文后，根据用户指令直接处理：

用户要求"总结" → Claude 直接总结原文
用户要求"翻译" → Claude 直接翻译原文
用户要求"提取要点" → Claude 直接提取
用户只说"转文字" → 呈现原文即可

故障排查

模型未找到: 检查 WHISPER_MODEL_PATH 环境变量或 ~/models/faster-whisper-large-v3-turbo/ 目录
转录为空: 检查音频是否有效，语言代码是否正确

Audio local

2 things to look at

SKILL.md

本地语音转文字

管线

执行步骤

1. 确认音频路径

2. 执行转录

3. 后续处理

故障排查

What ships with it: 8 files

models/

scripts/

Keep looking