I. Introduction
The Internet has democratized the production and distribution of music worldwide and has led to an explosion in the amount of music released online. To process such large amounts of audio data, we need better Music Information Retrieval (MIR). MIR is a multidisciplinary field that combines digital audio signal processing, pattern recognition, software engineering, and machine learning. MIR helps build better recommendation systems and helps classify songs based on the genre, mood, etc. MIR uses many different kinds of features to effectively classify audio files, one of which is the Mel-frequency Cepstral Coefficient(MFCC), which we will use in our research to classify genres from the FMA [1] dataset.