songsee

Generate spectrograms and audio feature visualizations from audio files.

Updated Apr 19, 2026

Search Tags:#analysis #visualization #audio #chroma #spectrogram #mfcc #mel

Ready to run

npx skills add https://github.com/gqf2008/hermez-ai --skill songsee-gqf2008

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/gqf2008/hermez-ai/tree/main/skills/media/songsee
Command: npx skills add https://github.com/gqf2008/hermez-ai --skill songsee-gqf2008

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audio professionals and researchers often need quick, repeatable visuals of sound to analyze structure, verify results, and document findings. songsee automates generating spectrograms and multi-panel audio feature visualizations directly from audio files.

Core Features & Use Cases

Generate standard spectrograms and additional visualizations (mel, chroma, MFCC, etc.) from audio inputs.
Produce multi-panel grids for comparative analysis and documentation.
Works as a CLI tool suitable for batch processing, debugging, and storytelling in audio workflows.

Quick Start

Run songsee on an audio file to generate a set of spectrograms and feature visualizations.

Frequently Asked Questions about songsee

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

FAQPage Schema

How do I generate a spectrogram from an audio file for analysis?▼

Generate spectrograms from audio files by running the songsee CLI tool, which natively decodes WAV and MP3 formats to produce visual outputs for audio analysis and documentation.

Can I visualize MFCC and mel features from WAV files in one batch?▼

Yes, you can visualize MFCC and mel features from WAV files in one batch. The CLI tool generates multi-panel grids combining various audio feature visualizations for comparative analysis and documentation.

Does this audio visualization tool require ffmpeg for MP3 files?▼

This audio visualization tool decodes WAV and MP3 natively without requiring ffmpeg, but optionally uses ffmpeg to process additional audio formats beyond the standard ones.

What is the best way to create multi-panel audio feature grids for documentation?▼

Create multi-panel audio feature grids for documentation by running a CLI tool that outputs spectrograms, mel, chroma, and MFCC visualizations, providing repeatable visual outputs for workflow storytelling and verification.

When should I use chroma and spectrogram visualizations in music production?▼

Use chroma and spectrogram visualizations in music production to analyze audio structure, verify production results, and create visual documentation. These features help debug workflows by visually representing sound characteristics.