Audio Genre Classification

Supervised and unsupervised machine learning algorithms are applied to classify music tracks into their respective genres.

Dataset:

 GTZAN Music Genre Dataset, of 1000 audio tracks each 30 seconds long. There are 10 genres represented, each containing 100 tracks. All the tracks are 22050 Hz Mono 16-bit audio files in .au format.

Techniques

• Kullback-Liebler (KL) Divergence
• K-Nearest Neighbors (k-NN)
• K-means clustering
• Multi-Class Support Vector Machine
• Convolutional Neural Networks