benchflow-ai/skillsbench/energy-calculator

Energy Calculator

Calculates per-second RMS (Root Mean Square) energy from audio files. Produces an energy profile that can be used for opening detection, pause detection, or other audio analysis tasks.

Use Cases

• Calculating audio energy for silence detection
• Preparing data for opening/pause detection
• Analyzing audio volume patterns

Usage

python3 /root/.claude/skills/energy-calculator/scripts/calc_energy.py \
    --audio /path/to/audio.wav \
    --output /path/to/energies.json

Parameters

• --audio: Path to input WAV file
• --output: Path to output JSON file
• --window-seconds: Window size for energy calculation (default: 1 second)

Output Format

{
  "sample_rate": 16000,
  "window_seconds": 1,
  "total_seconds": 600,
  "energies": [123.5, 456.7, 234.2, ...],
  "stats": {
    "min": 45.2,
    "max": 892.3,
    "mean": 234.5,
    "std": 156.7
  }
}

How It Works

1. Load audio file
2. Split into 1-second windows
3. Calculate RMS energy for each window: sqrt(mean(samples^2))
4. Output array of energy values

Dependencies

• Python 3.11+
• numpy

Example

# Calculate energy from extracted audio
python3 /root/.claude/skills/energy-calculator/scripts/calc_energy.py \
    --audio audio.wav \
    --output energies.json

Notes

• RMS energy correlates with perceived loudness
• Higher values = louder audio, lower values = quieter/silence
• Output can be used by opening-detector and pause-detector skills