Music genres is the taste, style and relax giving flow of a music. The genre of music refers to multiple types and categorization of music. The different types of famous music genre that we widely known are rock, jazz, reggae, classical, folk, blues, R & B, metal, dubstep, techno, country music, electro and pop. The key success of music in music industry is the genres of classified music that becomes a significant part of communicating music that provides bonding with relatively to human and masses of people. In contrast, the genre that falls under top-level style of rock are punk, indie, shoegaze, AOR and metal. They are basically subgenre of a music classification and it is important describing music to other people. In practical life, music is often used for multiple purposes due to physiological and social effects. Companies like Spotify, Soundcloud, Apple Music, Wynk & products like Shazam use music classification to provide their customers different flavour of music by recommending music they prefer to listen. we use python libraries such as Librosa and PyAudio library for audio processing in Python. We apply and use GTZAN dataset that is composed of 1000 audio tracks each 30-second-long representing 10 genres with 22050Hz mono audio file of 16bit in .au format for dataset. The functionality and working of music genre classification determine the help of Machine Learning algorithms. The algorithm such as KNN and artificial neural network (ANN) analyses and find out the similar similarity of genre features of music and classify it.

A community project to explore the boundaries of musical creativity, copyright, and the commons.

Algorithms and Blues

An algorithmic composer specialised in playing jazz and blues music using machine learning and genetic algorithms.

This predictor predicts 10 genres (Blues Classical Country Disco Hip-hop Jazz Metal Pop Reggae Rock) with Decision Tree as the training algorithm model and STFT for feature extraction

About Conquering DSA, one problem at a time. This repository is a collection of solved problems and my personal journey through the challenging yet rewarding world of data structures and algorithms. Let's tackle the "DSA Blues" together! Resources

Machine Learning model to classify audio (.wav) files into different genres such as pop, classical, hip-hop, country, jazz, blues, disco, metal, rock, reggae. The model uses GTZAN dataset and the KNN supervised machine learning algorithm to implement the same.