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name: songsee description: Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation. version: 1.0.0 author: community license: MIT metadata: hermes: tags: [Audio, Visualization, Spectrogram, Music, Analysis] homepage: https://github.com/steipete/songsee prerequisites: commands: [songsee]


songsee

Generate spectrograms and multi-panel audio feature visualizations from audio files.

Prerequisites

Requires Go:

go install github.com/steipete/songsee/cmd/songsee@latest

Optional: ffmpeg for formats beyond WAV/MP3.

Quick Start

# Basic spectrogram
songsee track.mp3

# Save to specific file
songsee track.mp3 -o spectrogram.png

# Multi-panel visualization grid
songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux

# Time slice (start at 12.5s, 8s duration)
songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg

# From stdin
cat track.mp3 | songsee - --format png -o out.png
t 12.5 --duration 8 -o slice.jpg

From stdin

cat track.mp3 | songsee - --format png -o out.png ```## Visualization Types

Use --viz with comma-separated values:

Type Description
spectrogram Standard frequency spectrogram
mel Mel-scaled spectrogram
chroma Pitch class distribution
hpss Harmonic/percussive separation
selfsim Self-similarity matrix
loudness Loudness over time
tempogram Tempo estimation
mfcc Mel-frequency cepstral coefficients
flux Spectral flux (onset detection)

Multiple --viz types render as a grid in a single image.

Common Flags

Flag Description
--viz Visualization types (comma-separated)
--style Color palette: classic, magma, inferno, viridis, gray
--width / --height Output image dimensions
--window / --hop FFT window and hop size
--min-freq / --max-freq Frequency range filter
--start / --duration Time slice of the audio
--format Output format: jpg or png
-o Output file path

Notes

  • WAV and MP3 are decoded natively; other formats require ffmpeg
  • Output images can be inspected with vision_analyze for automated audio analysis
  • Useful for comparing audio outputs, debugging synthesis, or documenting audio processing pipelines