songsee

Generate spectrograms and multi-panel audio feature visualizations via the songsee CLI.

1|Updated Apr 10, 2026
One-click install
npx skills add https://github.com/pertain99/openclaw-better --skill songsee-pertain99
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/pertain99/openclaw-better/tree/main/skills/songsee
Command: npx skills add https://github.com/pertain99/openclaw-better --skill songsee-pertain99

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Visualizing audio data can be tedious and time-consuming. songsee provides quick, automated generation of spectrograms and feature panels to facilitate analysis and interpretation.

Core Features & Use Cases

  • Generate spectrograms for individual tracks or batches to inspect frequency content over time.
  • Produce multi-panel visualizations combining features like mel spectrogram, chroma, hpss, self-similarity, loudness, and MFCCs for richer analysis.
  • Use in music research, speech processing, or audio QA workflows to quickly verify audio characteristics and quality.

Quick Start

Process an audio track into spectrogram visuals by running songsee on your audio file.

Frequently Asked Questions about songsee

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate spectrograms from audio files for signal visualization?

To generate spectrograms from audio files, use a CLI tool that converts standard audio formats into visual representations. This allows you to inspect frequency content over time for music research or speech processing.

Can I visualize multiple audio features like MFCCs and chroma in one view?

Yes, you can visualize multiple audio features in one view by producing multi-panel visualizations. These panels combine mel spectrograms, chroma, hpss, self-similarity, loudness, and MFCCs for richer signal analysis.

Does this spectrogram tool support batch processing for multiple audio tracks?

Yes, the spectrogram tool supports batch processing for multiple audio tracks. You can generate visualizations for individual tracks or batches to inspect frequency content across an entire dataset.

What is the best way to analyze audio characteristics for QA workflows?

The best way to analyze audio characteristics for QA workflows is by generating multi-panel visualizations combining features like loudness and self-similarity. This allows you to quickly verify audio quality and characteristics.

Do I need any specific dependencies to run the audio visualization CLI?

No specific dependencies are required to run the audio visualization CLI. The tool operates independently to convert standard audio formats into spectrograms and feature panels without external dependencies.