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audio-transcriber

Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/bingze00000/audio-transcriber-pro
Or

Purpose

This skill automates audio-to-text transcription with professional Markdown output, extracting rich technical metadata (speakers, timestamps, language, file size, duration) and generating structured meeting minutes and executive summaries. It uses Faster-Whisper or Whisper with zero configuration, working universally across projects without hardcoded paths or API keys.

Inspired by tools like Plaud, this skill transforms raw audio recordings into actionable documentation, making it ideal for meetings, interviews, lectures, and content analysis.

When to Use

Invoke this skill when:

  • User needs to transcribe audio/video files to text
  • User wants meeting minutes automatically generated from recordings
  • User requires speaker identification (diarization) in conversations
  • User needs subtitles/captions (SRT, VTT formats)
  • User wants executive summaries of long audio content
  • User asks variations of "transcribe this audio", "convert audio to text", "generate meeting notes from recording"
  • User has audio files in common formats (MP3, WAV, M4A, OGG, FLAC, WEBM)

Workflow

Step 0: Discovery (Auto-detect Transcription Tools)

Objective: Identify available transcription engines without user configuration.

Actions:

Run detection commands to find installed tools:

# Check for Faster-Whisper (preferred - 4-5x faster)
if python3 -c "import faster_whisper" 2>/dev/null; then
    TRANSCRIBER="faster-whisper"
    echo "✅ Faster-Whisper detected (optimized)"
# Fallback to original Whisper
elif python3 -c "import whisper" 2>/dev/null; then
    TRANSCRIBER="whisper"
    echo "✅ OpenAI Whisper detected"
else
    TRANSCRIBER="none"
    echo "⚠️  No transcription tool found"
fi

# Check for ffmpeg (audio format conversion)
if command -v ffmpeg &>/dev/null; then
    echo "✅ ffmpeg available (format conversion enabled)"
else
    echo "ℹ️  ffmpeg not found (limited format support)"
fi

If no transcriber found:

Offer automatic installation using the provided script:

echo "⚠️  No transcription tool found"
echo ""
echo "🔧 Auto-install dependencies? (Recommended)"
read -p "Run installation script? [Y/n]: " AUTO_INSTALL

if [[ ! "$AUTO_INSTALL" =~ ^[Nn] ]]; then
    # Get skill directory (works for both repo and symlinked installations)
    SKILL_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
    
    # Run installation script
    if [[ -f "$SKILL_DIR/scripts/install-requirements.sh" ]]; then
        bash "$SKILL_DIR/scripts/install-requirements.sh"
    else
        echo "❌ Installation script not found"
        echo ""
        echo "📦 Manual installation:"
        echo "  pip install faster-whisper  # Recommended"
        echo "  pip install openai-whisper  # Alternative"
        echo "  brew install ffmpeg         # Optional (macOS)"
        exit 1
    fi
    
    # Verify installation succeeded
    if python3 -c "import faster_wh...

Metadata

Stars4473
Views1
Updated2026-05-01
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-bingze00000-audio-transcriber-pro": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags

#[audio#transcription#whisper#meeting-minutes#speech-to-text]
Safety NoteClawKit audits metadata but not runtime behavior. Use with caution.