Generate mel spectrogram, chromagram, and MFCC plots from audio files.
npx skills add https://github.com/taracodlabs/aiden --skill songsee-taracodlabs
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/taracodlabs/aiden/tree/main/skills/songsee Command: npx skills add https://github.com/taracodlabs/aiden --skill songsee-taracodlabs
Visualize audio content to reveal spectral and timbral structure for quick interpretation.
Run the analysis on an audio file to generate mel spectrogram, chromagram, and MFCC plots.
High-intent search queries and answers about installing and using this skill.
Generate MFCC plots from audio by extracting spectral features with librosa. This Skill produces PNG visualizations of mel-frequency cepstral coefficients to reveal timbral structure for speech processing and music analysis.
Visualize chromagrams to compare recordings by extracting pitch-class profiles with librosa. This Skill generates PNG plots that highlight frequency and timbral differences between audio files for music analysis workflows.
This audio visualization approach requires both librosa and matplotlib to function. Librosa extracts spectral features like MFCC and chromagrams, while matplotlib renders the resulting data into PNG plots for analysis.
Debug audio using spectral plots by generating visualizations like mel spectrograms and chromagrams to inspect anomalies. This Skill creates PNG outputs that reveal underlying spectral and timbral structure for quick debugging.
The generated audio plots are suitable for machine learning workflows as static PNG outputs. They visualize mel spectrograms and MFCC data to help interpret spectral features for data analysis and model debugging.
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