songsee

Generate spectrograms and audio feature visualizations from WAV and MP3 files.

Updated Jun 15, 2026

Search Tags:#cli #visualization #audio #spectrogram #mfcc #mel

Ready to run

npx skills add https://github.com/faramirezs/talking_printer --skill songsee-faramirezs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/faramirezs/talking_printer/tree/main/hermes-agent/skills/media/songsee
Command: npx skills add https://github.com/faramirezs/talking_printer --skill songsee-faramirezs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generate spectrograms and multi-panel audio feature visualizations from audio files, enabling quick inspection of spectral content and feature trends.

Core Features & Use Cases

Visualize: generate spectrograms, Mel, Chroma, MFCC, and other feature visualizations from WAV/MP3 inputs.
CLI-first workflow: use a single command to create informative visuals for music analysis, research, and teaching.
Use Case: researchers can compare tracks by visualizing multiple features side-by-side to identify similarities and differences.

Quick Start

Generate a spectrogram for your track.mp3 using the songsee CLI and save the output as an image.

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 workflow?▼

Generate audio spectrograms from MP3 files by running a CLI command that processes the input track and saves the visualization as an image. You can use CLI flags to control the output format and specific feature displays.

What audio feature visualizations can I create for music analysis?▼

Audio feature visualizations for music analysis include spectrogram, mel, chroma, hpss, selfsim, loudness, tempogram, and mfcc plots. These multi-panel visuals allow you to inspect spectral content and compare feature trends across tracks.

Do I need a Go toolchain to generate audio spectrograms from the command line?▼

A Go toolchain is required for installation to generate audio spectrograms from the command line. Optional ffmpeg support is also available to handle additional audio processing tasks within your workflow.

What's the best way to compare audio tracks by visualizing multiple features side-by-side?▼

The best way to compare audio tracks is by generating multi-panel visualizations of features like mfcc, chroma, and mel from WAV or MP3 inputs. This allows researchers to inspect spectral content and identify similarities side-by-side.

Does the CLI audio visualizer work with both WAV and MP3 inputs?▼

The CLI audio visualizer works with both WAV and MP3 inputs, allowing you to generate spectrograms and feature plots like loudness and tempogram from these common audio formats for research and teaching.