---
name: songsee
version: 1.0.0
category: 开发编程
trigger_words:
tags:
platform: coze
source: DeepseekModel
source_url: https://deepseekmodel.com/skill?id=nousresearch-hermes-agent-skills-media-songsee-skill-md
---

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 : 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