dennisvdang/Chroma-based-Music-Segmentation
Project repository containing code, proof of concept, and visualizations for using Chromagram Self-Similarity Matrices (SSMs) for segmenting music into its structural components.
This project helps music analysts and researchers automatically break down songs into structural parts like intros, verses, and choruses. It takes an audio file as input and outputs a segmented structure of the song, identifying repeating sections. Musicologists, composers, and anyone studying musical form would find this useful.
No commits in the last 6 months.
Use this if you need to automatically identify the different sections within a piece of music.
Not ideal if you are looking for chord transcriptions or detailed tempo analysis, as this focuses on structural segmentation.
Stars
11
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Mar 21, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/dennisvdang/Chroma-based-Music-Segmentation"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
mlachmish/MusicGenreClassification
Classify music genre from a 10 second sound stream using a Neural Network.
HareeshBahuleyan/music-genre-classification
Recognizing the genre of music files using machine learning and deep learning models
despoisj/DeepAudioClassification
Finding the genre of a song with Deep Learning
serkansulun/midi-emotion
Generates multi-instrument symbolic music (MIDI), based on user-provided emotions from...
cobanov/audio-genre-detection
Categorize audio files by genre effortlessly. Use Dockerized environment and API to classify...