Generate spectrograms and multi-panel audio feature visualizations from input files.
npx skills add https://github.com/dingdyan/openclaw-workspace-v2 --skill songsee-dingdyan
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/dingdyan/openclaw-workspace-v2/tree/main/skills/songsee Command: npx skills add https://github.com/dingdyan/openclaw-workspace-v2 --skill songsee-dingdyan
Songsee helps you quickly visualize what is happening inside an audio file so you can analyze timbre, rhythm, and audio characteristics without manually running complex DSP pipelines.
Example use case: You have a song segment where vocals change abruptly and need to compare chroma, loudness, and MFCC behavior across a short time range; generate a multi-panel output for the full track or a focused slice.
Generate a spectrogram for your audio file by running: songsee track.mp3 -o output.png
High-intent search queries and answers about installing and using this skill.
To generate an audio spectrogram, you can use the songsee CLI to decode your input file and render a time-frequency visual output by running a command like songsee track.mp3 -o output.png.
Yes, you can visualize multiple DSP-derived audio features together by rendering multi-panel outputs that display MFCC, chroma, loudness, and tempogram views side-by-side for comparative analysis.
You can inspect a specific time window in an audio spectrogram by using targeted time slicing to focus on exact segments, allowing you to analyze events like intros, beats, or transitions.
You need ffmpeg for audio feature visualization when analyzing MP3 files that require decoding, although the CLI also supports native WAV file processing without additional dependencies.
The best way to compare loudness and MFCC behavior is by generating a multi-panel audio feature visualization that renders these DSP-derived characteristics together for a targeted time slice.
Yes, you can configure the frequency range and windowing parameters when creating spectrograms for music information retrieval to customize the visual output for your specific analysis needs.
dsactivi-2Generate spectrograms and feature-panel visualizations from audio files using the songsee CLI.
AissenLiuGenerate spectrograms and multi-panel audio feature visualizations from audio files via CLI.
yunseo-kimGenerate spectrograms and feature-panel visualizations from audio files.
coltonbattsGenerate spectrograms and feature-panel visualizations from audio files using the songsee CLI.
