Generate spectrograms and multi-panel audio feature visualizations from WAV/MP3 files.
npx skills add https://github.com/Aevonix/colony-ai --skill songsee-aevonix
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/Aevonix/colony-ai/tree/main/skills/media/songsee Command: npx skills add https://github.com/Aevonix/colony-ai --skill songsee-aevonix
Generate spectrograms and multi-panel audio feature visualizations from audio files to accelerate analysis, debugging, and documentation of audio workflows.
Visualize audio by generating a spectrogram from input track.mp3.
High-intent search queries and answers about installing and using this skill.
Generating a spectrogram from an audio file involves processing WAV or MP3 inputs to visualize frequency content over time. This requires a Go toolchain and the songsee command to execute the visualization workflow.
For music production debugging, you can visualize audio features such as mel, chroma, MFCC, tempogram, loudness, and flux. Generating multi-panel grids of these features helps compare pitch content, tempo, and timbre during track analysis.
You need ffmpeg only as an optional dependency to process additional audio formats beyond native support. The core visualization functionality relies on a Go toolchain and the songsee command to handle WAV and MP3 inputs.
Yes, you can create multi-panel grids combining multiple feature types like spectrogram, chroma, and MFCC for quick visual comparisons. This allows you to analyze pitch content, tempo, and timbre within a single consolidated visualization output.
The best way to document an audio processing pipeline for a release is to generate multi-panel audio feature visualizations from your files. Visualizing spectrograms, chroma, and loudness provides clear visual documentation of the track's processing characteristics.
erichowensRender real-time audio-responsive WebGL visualizations using Butterchurn presets and Web Audio FFT data.
quiznatGenerate spectrograms and multi-panel audio feature visualizations from audio files.
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kevinnftGenerate spectrogram, Mel, and MFCC visualizations from audio files.
