energy-calculator
Calculate per-second RMS energy from audio files. Use when you need to analyze audio volume patterns, prepare data for silence/pause detection, or create an energy profile for audio analysis tasks.
- License 许可
- Apache-2.0
- 最近更新
- 2026-04-21
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- ★ 0
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01 前言 Front Matter
- name
- energy-calculator
- description
- Calculate per-second RMS energy from audio files. Use when you need to analyze audio volume patterns, prepare data for silence/pause detection, or create an energy profile for audio analysis tasks.
02 资源文件 1
- 脚本scripts/calc_energy.py2.2 KB
03 SKILL.md 正文
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
- Load audio file
- Split into 1-second windows
- Calculate RMS energy for each window:
sqrt(mean(samples^2)) - 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
04 同仓库更多 Skills
data-reconciliation
暂无简介
speech-to-text
Transcribe video to timestamped text using Whisper tiny model (pre-installed).
video-processor
Process videos by removing segments and concatenating remaining parts. Use when you need to remove detected pauses/openings from videos, create highlight reels, or batch process segment removals using ffmpeg filter_complex.
silence-detector
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).
segment-combiner
Combine multiple segment detection results into a unified list. Use when you need to merge segments from different detectors, prepare removal lists for video processing, or consolidate detection outputs.
report-generator
Generate compression reports for video processing. Use when you need to create structured JSON reports with duration statistics, compression ratios, and segment details after video processing.