Generate spectrogram and audio feature visualizations from audio files.
npx skills add https://github.com/TitoPrausee/nexus-toti --skill songsee-titoprausee
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/TitoPrausee/nexus-toti/tree/main/data/skills/media/songsee Command: npx skills add https://github.com/TitoPrausee/nexus-toti --skill songsee-titoprausee
songsee removes the guesswork from listening-only audio review by turning audio files into visual representations that make frequency content, timing, and structure easier to inspect.
Use songsee to generate a spectrogram image from your audio file and save it to the output path you choose.
High-intent search queries and answers about installing and using this skill.
Generate spectrograms from MP3 or WAV files by processing the audio through a visual analysis tool that extracts frequency content and timing into a clear image output. It creates standard or mel-scaled views for fast audio inspection.
Visualize MFCC and chroma features in one multi-panel output by combining chroma, tempogram, flux, loudness, self-similarity, and HPSS views. This consolidates audio feature visualizations for deeper comparison and music production debugging.
You need ffmpeg to visualize non-native audio formats. The system requires CLI access for native decoding and uses optional ffmpeg support to process and visualize unsupported audio files for your analysis workflow.
Debug music production audio visually by generating spectrogram and audio feature visualizations that turn listening-only review into clear visual representations. It makes frequency content, timing, and structure easier to inspect.
You can configure time slicing, panels, and output settings for audio spectrograms. The tool processes decoded audio formats with configurable parameters to generate tailored visual documentation of audio processing results.
Mel-scaled spectrogram analysis helps with dataset review by transforming audio files into visual representations of frequency content. It removes guesswork from listening-only review, making dataset structure and audio features easier to inspect.
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syxscottGenerate spectrograms and feature-panel visualizations from audio files with the songsee CLI.
