/music-timbre — Timbre & Spectral Analysis
music-timbre
Analyze timbre — MFCC, spectral features, loudness, source separation
SKILL.md
Full skill instructions
/music-timbre — Timbre & Spectral Analysis
Extract timbral and spectral characteristics: MFCC coefficients, spectral centroid/bandwidth/rolloff, loudness (LUFS), dynamic range, brightness, warmth, and optionally separate audio sources.
Usage
/music-timbre <audio_file_path>
Steps
- Validate the audio file path
- Run timbre analysis:
python3 -m music_analyzer timbre "<audio_file_path>"
Add --no-separation to skip Demucs source separation.
- Present results:
- Brightness: Score 0-1 (higher = brighter timbre)
- Warmth: Score 0-1 (higher = more low-frequency energy)
- Dynamic Range: Estimated in dB
- Loudness: LUFS (if pyloudnorm available)
- MFCC Summary: 13-coefficient means
- Stems: Paths to separated vocals/drums/bass/other (if demucs ran)
Output Fields
| Field | Description |
|---|---|
mfcc | MFCC means and stds |
spectral | Centroid, bandwidth, rolloff, ZCR |
loudness_lufs | Integrated loudness in LUFS |
dynamic_range_db | Dynamic range in dB |
brightness | Brightness score 0-1 |
warmth | Warmth score 0-1 |
stems | Separated stem file paths (if available) |