Silence Detector

name silence-detector description Detect initial silence segments in audio/video using energy-based analysis. Use when you need to find low-energy periods at the start of recordings (title slides, setup time, pre-roll silence). Silence Detector Detects initial silence segments by analyzing pre-computed energy data. Finds the transition point from low-energy silence to higher-energy content. Use Cases Finding initial silence in recordings Detecting pre-roll silence before content Identifying setup/title card periods Usage python3 /root/.claude/skills/silence-detector/scripts/detect_silence.py
--energies /path/to/energies.json
--output /path/to/silence.json Parameters --energies : Path to energy JSON file (from energy-calculator) --output : Path to output JSON file --threshold-multiplier : Energy threshold multiplier (default: 1.5) --initial-window : Seconds for baseline calculation (default: 60) --smoothing-window : Moving average window (default: 30) Output Format { "method" : "energy_threshold" , "segments" : [ { "start" : 0 , "end" : 120 , "duration" : 120 } ] , "total_segments" : 1 , "total_duration_seconds" : 120 , "parameters" : { "threshold_multiplier" : 1.5 , "initial_window" : 60 , "smoothing_window" : 30 } } How It Works Load pre-computed energy data Calculate baseline from first N seconds (likely silent) Apply smoothing with moving average Find where smoothed energy exceeds baseline x multiplier Dependencies Python 3.11+ numpy Example

Detect initial silence from energy data