songsee

Name: songsee
Availability: InStock
Author: DifanaDAP

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

Updated Apr 29, 2026

Search Tags:#CLI tool #spectrogram #audio analysis #audio visualization #audio feature extraction

Ready to run

npx skills add https://github.com/DifanaDAP/hermes-backup --skill songsee-difanadap

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/DifanaDAP/hermes-backup/tree/main/workspace/skills/media/songsee
Command: npx skills add https://github.com/DifanaDAP/hermes-backup --skill songsee-difanadap

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires go, ffmpeg, and includes scripts (resource) and references (resource) components.

What problem does it solve?

songsee solves the problem of manually generating audio spectrograms and multi-panel audio feature visualizations, providing an efficient CLI tool for audio analysis.

Core Features & Use Cases

CLI Interface: Offers a simple command-line interface for generating audio visualizations.
Feature Extraction: Extracts various audio features like mel, chroma, MFCC, and more.
Visualization Types: Provides multiple visualization types such as spectrograms, mel-scaled spectrograms, and pitch class distribution.
Use Case: Ideal for audio engineers, musicians, and researchers who need to quickly visualize audio data for analysis.

Quick Start

Generate a spectrogram for 'track.mp3' using the songsee command.

Frequently Asked Questions about songsee

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

FAQPage Schema

How do I generate an audio spectrogram from an mp3 file using a CLI?▼

You can generate an audio spectrogram from an mp3 file by running a single command-line instruction. The tool processes the audio file and outputs a visual spectrogram representation for analysis.

What audio features can I visualize for audio analysis?▼

You can visualize various audio features including mel-scaled spectrograms, chroma, MFCC, and pitch class distribution. These multi-panel visualizations help analyze different characteristics of the audio data.

Do I need ffmpeg installed to extract audio features and generate visualizations?▼

You need the Go environment installed to run the tool, and ffmpeg is required optionally. Ffmpeg is specifically necessary for processing certain audio formats during feature extraction and visualization.

What is the best way to visualize mel and chroma features for music tracks?▼

The best way to visualize mel and chroma features is using a dedicated CLI tool that extracts these characteristics and generates multi-panel visualizations. This provides an efficient method for audio analysis.

Can I use this audio analysis tool for batch processing multiple audio files?▼

The tool operates via a command-line interface designed for generating audio visualizations from audio files. It provides a simple interface for extracting features and visualizing spectrograms.

Why does my spectrogram generation fail when processing certain audio formats?▼

Spectrogram generation may fail for certain audio formats if ffmpeg is not installed. Ffmpeg is an optional dependency required to process specific audio formats before feature extraction and visualization.