Generate spectrograms and feature visualizations from audio files using songsee.
npx skills add https://github.com/Gitnapp/Skills --skill songsee-gitnapp
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/Gitnapp/Skills/tree/main/media/songsee Command: npx skills add https://github.com/Gitnapp/Skills --skill songsee-gitnapp
This Skill helps analyze audio files by transforming raw sound into visual representations that reveal frequency, pitch, rhythm, and other audio characteristics.
Use the songsee skill to generate a spectrogram visualization from the provided audio file and save the result as an image.
High-intent search queries and answers about installing and using this skill.
You generate an audio spectrogram by using this Skill to process your audio file and output a configurable image. It transforms raw sound into visual representations revealing frequency, pitch, and rhythm characteristics for music analysis.
Besides standard spectrograms, you can visualize mel spectrograms, chroma, MFCC, loudness, and tempo. These multi-panel feature views help inspect detailed audio characteristics for synthesis debugging and signal processing workflows.
Yes, visualizing audio features requires the songsee command-line tool. It enables configurable audio inspection workflows, allowing you to specify time slices, output formats, visualization types, and frequency ranges for your analysis.
Yes, audio visualization is fully configurable through the command-line tool. You can set specific time slices, adjust frequency ranges, and select output formats to isolate and inspect targeted signal processing characteristics.
The best way to debug audio synthesis outputs is generating multi-panel feature views like spectrograms and MFCC images. This visual analysis reveals frequency and rhythm anomalies in the audio signal that raw sound conceals.
the-open-agentGenerate spectrograms and feature panels from local MP3 or WAV files.
AlvaroBianoGenerate spectrogram, mel, chroma, hpss, mfcc visualizations from audio files to PNG/JPG using songsee CLI.
erichowensRender real-time audio-responsive WebGL visualizations using Butterchurn presets and Web Audio FFT data.
gigagiovaGenerate spectrograms and multi-panel audio feature visualizations from audio files via CLI.
