Chord Mini

Chord Mini

ChordMini is an open-source music analysis platform powered by AI that provides chord recognition, beat detection, and synchronized lyrics for both YouTube videos and audio files.
https://www.chordmini.me/?ref=producthunt
Chord Mini

Product Information

Updated:Aug 20, 2025

What is Chord Mini

ChordMini is an advanced music analysis tool that combines artificial intelligence and machine learning to help users understand and visualize musical elements. As an open-source project developed at California State University, Fullerton, it offers comprehensive analysis of songs including chord progressions, beat patterns, and musical structure. The platform supports both direct audio uploads and YouTube video analysis, making it accessible for musicians, students, and music enthusiasts.

Key Features of Chord Mini

ChordMini is an advanced open-source music analysis platform that combines AI-powered chord recognition, beat detection, and visualization capabilities. It uses multiple machine learning models to analyze songs from YouTube videos or audio files, providing accurate chord progressions, guitar chord diagrams, beat tracking, and synchronized visualization. The platform supports comprehensive chord detection including major, minor, 7th chords, and their inversions, while offering real-time playback synchronization and interactive navigation.
AI-Powered Chord Recognition: Uses multiple AI models (Chord-CNN-LSTM and BTC) to accurately detect and identify various chord types with enharmonic correction and context-aware interpretation using LLM
Intelligent Beat Detection: Employs Beat-Transformer and Madmom algorithms for precise timing analysis, including BPM detection, time signature identification, and downbeat detection
Interactive Visualization: Provides dynamic chord grids and beat maps that synchronize with audio playback, featuring measure-based layout and responsive design
Multiple Input Sources: Supports analysis from both YouTube links and direct audio file uploads, making it versatile for different user needs

Use Cases of Chord Mini

Music Education: Helps students and teachers analyze songs for learning chord progressions and musical structure
Music Production: Assists producers and composers in analyzing reference tracks and understanding chord structures
Live Performance: Enables musicians to quickly learn and visualize song structures for performance preparation
Music Research: Supports academic research in music theory and analysis through detailed chord and beat detection

Pros

Open-source and free to use
Comprehensive music analysis capabilities
Support for multiple input sources and chord types

Cons

Server maintenance not guaranteed long-term
CPU-based computation is slower than GPU
Requires stable internet connection for analysis

How to Use Chord Mini

Access ChordMini: Visit the ChordMini website at chordmini.me or use the open-source application
Input Music Source: Either paste a YouTube URL, search for a song by keywords, or upload your own audio file for analysis
Select Analysis Options: Choose the desired AI models for chord recognition (Chord-CNN-LSTM or BTC) and beat detection algorithms
Start Analysis: Click the analyze button to begin processing your selected music. The system will detect chords, beats, and tempo
View Chord Progression: Once analysis is complete, view the interactive chord grid showing the progression synchronized with the audio
Explore Guitar Diagrams: Click on any chord in the progression to see its corresponding guitar chord diagram
Navigate Playback: Use the interactive beat map to navigate through the song - click any beat to jump to that section
Review Analysis Details: Check the detected BPM, time signature, and other musical elements identified by the system
Save or Share Results: Save your analysis results or share them with others in the ChordMini community

Chord Mini FAQs

ChordMini is an open-source music analysis platform that uses AI to provide chord recognition, beat detection, and synchronized lyrics for audio files and YouTube videos.

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