Generate spectrograms and feature-panel visualizations from audio files with the songsee CLI.
npx skills add https://github.com/syxscott/PaleoClaw --skill songsee-syxscott
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/syxscott/PaleoClaw/tree/main/skills/songsee Command: npx skills add https://github.com/syxscott/PaleoClaw --skill songsee-syxscott
This Skill generates detailed spectrograms and feature visualizations from audio files, allowing for in-depth analysis of sound patterns.
Generate a spectrogram for the audio file track.mp3.
High-intent search queries and answers about installing and using this skill.
To generate a spectrogram from an audio file, you can use this Skill to process audio files and output visual representations of audio frequencies over time in PNG or JPG format.
Besides a basic spectrogram, you can visualize audio features like Mel spectrograms, chroma, loudness, MFCCs, HPSS, self-similarity, tempograms, and spectral flux.
Yes, you can extract specific time segments from audio recordings for focused analysis by utilizing the time-based slicing functionality during the visualization process.
Audio visualization outputs are supported in PNG and JPG image formats, allowing you to save and export your generated spectrograms and feature-panel visualizations.
To visualize the harmonic structure of a musical piece, you can analyze the audio file using the chroma feature extraction option to generate detailed visual representations.
No external dependencies are required to extract audio features for visualization, as the Skill operates independently using the songsee CLI to process and generate image outputs.
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