Automatic Mood Tracking in Audio Music

Abstract

In this thesis, music emotion recognition is approached, having detection of mood changes over a song as the main focus. The first semester served entirely to gain knowledge on the area and a to produce an initial design. This strong theoretical knowledge was further developed during the second semester, serving as a starting point to build a music analysis Qt application, based on the Thayer's model of mood, using on Marsyas for feature extraction and libSVM library for classification and regression. Several experimental tests were run to study different approaches and the respective results.