Generate spectrograms and feature-panel visualizations from audio files.
npx skills add https://github.com/MaxSaiets/myOpenCL --skill songsee-maxsaiets
Please help me install this Agent Skill. Skill: songsee Source: https://github.com/MaxSaiets/myOpenCL/tree/main/openclaw/skills/songsee Command: npx skills add https://github.com/MaxSaiets/myOpenCL --skill songsee-maxsaiets
Turning audio into actionable visual insights by generating spectrograms and feature-panel visualizations automatically.
Run songsee on an audio file to produce the default spectrogram visualization.
High-intent search queries and answers about installing and using this skill.
You can generate an audio spectrogram by running the CLI tool on common formats like WAV and MP3 to produce visual representations for quick spectral analysis.
A feature-panel visualization maps musical features from audio files to enable rapid sonic analysis, allowing you to monitor audio characteristics or compare tracks during research and content creation.
Yes, the tool supports batch runs for spectrogram creation, allowing you to process multiple audio files at once for streamlined comparison and validation of audio processing pipelines.
Yes, the tool supports audio decoding natively with an ffmpeg fallback, ensuring it can process common formats like MP3 and WAV for spectrogram and feature-panel generation.
Yes, you can configure windowing and frequency ranges to customize your spectrogram visualizations, adapting the sonic analysis output to specific research or music analysis requirements.
To inspect spectral content across streaming audio contexts, use this CLI tool which supports streaming contexts alongside single-file processing and batch runs for continuous spectrogram visualization.
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