Project

A Mood-Based Music Classification and Exploration System

Mood classification is very subjective. There have been many psychological studies performed throughout the past century relating to music and emotion, and as a result there exist many different representations of human emotion. This work proposes to utilize the best possible psychological model of emotion by incorporating the findings of these studies into an innovative front-end for a digital music library where music can be queried, browsed, and explored by mood, rather than artist, album, or genre. With the use of state-of-the-art audio and textual analysis tools this work proposes to automatically and accurately classify music by mood.

Mood classification is very subjective. There have been many psychological studies performed throughout the past century relating to music and emotion, and as a result there exist many different representations of human emotion. This work proposes to utilize the best possible psychological model of emotion by incorporating the findings of these studies into an innovative front-end for a digital music library where music can be queried, browsed, and explored by mood, rather than artist, album, or genre. With the use of state-of-the-art audio and textual analysis tools this work proposes to automatically and accurately classify music by mood.