songsee

Generate spectrograms and visualizations from audio files.

Updated Jun 19, 2026

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

Ready to run

npx skills add https://github.com/AnandaAnugrahHandyanto/savarez_agent --skill songsee-anandaanugrahhandyanto

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audio researchers and developers spend time generating and visualizing audio feature representations; songsee streamlines this by producing spectrograms and related visualizations directly from audio files.

Core Features & Use Cases

Generate standard spectrograms (spectrogram, mel, chroma) and advanced visualizations (MFCC, loudness, tempogram).
Quickly compare multiple visualizations in a single run for analysis, debugging, or demonstration purposes.
Use Case: You have a track and want a quick multi-panel visualization to audit tonal content and rhythm.

Quick Start

Create a multi-panel visualization for an audio file using songsee.

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 using a CLI?▼

Songsee generates multi-panel spectrogram visualizations from audio files to assist in analyzing tonal content and rhythm. It outputs standard spectrograms, mel, and chroma images, allowing you to quickly audit and compare audio features in a single run.

Can I generate mel spectrograms and MFCC visualizations for multiple audio tracks?▼

Yes, songsee generates mel spectrograms and MFCC visualizations for individual tracks or large audio collections. It supports batch processing to quickly compare multiple audio feature representations in a single automated run for music analysis.

Do I need Go and ffmpeg to run a CLI audio spectrogram generator?▼

Yes, you need Go to build and run the songsee CLI for generating spectrograms. Ffmpeg may also be required to process non-native audio formats, and the tool supports Linux, macOS, and Windows operating systems.

What is the best way to visualize chroma and tempogram features for music analysis?▼

Using a CLI tool like songsee to generate multi-panel visualizations is an efficient way to visualize chroma and tempogram features for music analysis. It allows you to compare tonal content and rhythm representations side-by-side in image formats like PNG.

Does songsee support Windows for automated audio visualization?▼

Yes, songsee supports Windows for automated audio visualization. It also runs on Linux and macOS, requiring Go to build the CLI and potentially ffmpeg to handle non-native audio formats during the visualization process.