ListenHub Asr
by @0xfango
Transcribe audio files to text using local speech recognition. Triggers on: "转录", "transcribe", "语音转文字", "ASR", "识别音频", "把这段音频转成文字".
clawhub install marswave-asr📖 About This Skill
name: asr metadata: openclaw: emoji: "🎙️" requires: tools: ["coli"] description: | Transcribe audio files to text using local speech recognition. Triggers on: "转录", "transcribe", "语音转文字", "ASR", "识别音频", "把这段音频转成文字".
When to Use
When NOT to Use
/tts)/podcast or /explainer)Purpose
Transcribe audio files to text using coli asr, which runs fully offline via local
speech recognition models. No API key required. Supports Chinese, English, Japanese,
Korean, and Cantonese (sensevoice model) or English-only (whisper model).
Run coli asr --help for current CLI options and supported flags.
Hard Constraints
shared/config-pattern.md before any interactionshared/common-patterns.md for interaction patternsInteraction Flow
Step 0: Prerequisites Check
Before config setup, silently check the environment:
COLI_OK=$(which coli 2>/dev/null && echo yes || echo no)
FFMPEG_OK=$(which ffmpeg 2>/dev/null && echo yes || echo no)
MODELS_DIR="$HOME/.coli/models"
MODELS_OK=$([ -d "$MODELS_DIR" ] && ls "$MODELS_DIR" | grep -q sherpa && echo yes || echo no)
| Issue | Action |
|-------|--------|
| coli not found | Block. Tell user to run npm install -g @marswave/coli first |
| ffmpeg not found | Warn (WAV files still work). Suggest brew install ffmpeg / sudo apt install ffmpeg |
| Models not downloaded | Inform user: first transcription will auto-download models (~60MB) to ~/.coli/models/ |
If coli is missing, stop here and do not proceed.
Step 0: Config Setup
Follow shared/config-pattern.md Step 0.
Initial defaults:
# 当前目录:
mkdir -p ".listenhub/asr"
echo '{"model":"sensevoice","polish":true}' > ".listenhub/asr/config.json"
CONFIG_PATH=".listenhub/asr/config.json"全局:
mkdir -p "$HOME/.listenhub/asr"
echo '{"model":"sensevoice","polish":true}' > "$HOME/.listenhub/asr/config.json"
CONFIG_PATH="$HOME/.listenhub/asr/config.json"
Config summary display:
当前配置 (asr):
模型:sensevoice / whisper-tiny.en
润色:开启 / 关闭
Setup Flow (first run or reconfigure)
Ask in order:
1. model: "默认使用哪个语音识别模型?" - "sensevoice(推荐)" — 支持中英日韩粤,可检测语言、情绪、音频事件 - "whisper-tiny.en" — 仅英文
3. polish: "转录后由 AI 润色文本?(修正标点、去语气词、提升可读性)"
- "是(推荐)" → polish: true
- "否,保留原始转录" → polish: false
Save all answers at once after collecting them.
Step 1: Get Audio File
If the user hasn't provided a file path, ask:
> "请提供要转录的音频文件路径。"
Verify the file exists before proceeding.
Step 2: Confirm
准备转录: 文件:{filename}
模型:{model}
润色:{是 / 否}
继续?
Step 3: Transcribe
Run coli asr with JSON output (to get metadata):
coli asr -j --model {model} "{file}"
On first run, coli will automatically download the required model. This may take a
moment — inform the user if models haven't been downloaded yet.
Parse the JSON result to extract text, lang, emotion, event, duration.
Step 4: Polish (if enabled)
If polish is true, take the raw text from the transcription result and rewrite
it to fix punctuation, remove filler words, and improve readability. Preserve the
original meaning and speaker intent. Do not summarize or paraphrase.
Step 5: Present Result
Display the transcript directly in the conversation:
转录完成{transcript text}
─────────────────
语言:{lang} · 情绪:{emotion} · 时长:{duration}s
If polished, show the polished version with a note that it was AI-refined. Offer to show the raw original on request.
Step 6: Export as Markdown (optional)
After presenting the result, ask:
Question: "保存为 Markdown 文件到当前目录?"
Options:
- "是" — save to current directory
- "否" — done
If yes, write {audio-filename}-transcript.md to the current working directory
(where the user is running Claude Code). The file should contain the transcript text
(polished version if polish was enabled), with a front-matter header:
---
source: {original audio filename}
date: {YYYY-MM-DD}
model: {model used}
duration: {duration}s
lang: {detected language}
{transcript text}
Composability
Examples
> "帮我转录这个文件 meeting.m4a"
1. Check prerequisites
2. Read config
3. Confirm: meeting.m4a, sensevoice, polish on
4. Run coli asr -j --model sensevoice "meeting.m4a"
5. Polish the raw text
6. Display inline
> "transcribe interview.wav, no polish"
1. Check prerequisites
2. Read config
3. Override polish to false for this session
4. Run coli asr -j --model sensevoice "interview.wav"
5. Display raw transcript inline
⚡ When to Use
💡 Examples
> "帮我转录这个文件 meeting.m4a"
1. Check prerequisites
2. Read config
3. Confirm: meeting.m4a, sensevoice, polish on
4. Run coli asr -j --model sensevoice "meeting.m4a"
5. Polish the raw text
6. Display inline
> "transcribe interview.wav, no polish"
1. Check prerequisites
2. Read config
3. Override polish to false for this session
4. Run coli asr -j --model sensevoice "interview.wav"
5. Display raw transcript inline