/songsee

name: songsee
description: "Audio spectrograms/features (mel, chroma, MFCC) via CLI."
version: 1.0.0
author: community
license: MIT
platforms: [linux, macos, windows]
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](https://go.dev/doc/install):

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

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