  Music is one of the basic human needs for recreation and entertainment. As
song files are digitalized now a days, and digital libraries are expanding
continuously, which makes it difficult to recall a song. Thus need of a new
classification system other than genre is very obvious and mood based
classification system serves the purpose very well. In this paper we will
present a well-defined architecture to classify songs into different mood-based
categories, using audio content analysis, affective value of song lyrics to map
a song onto a psychological-based emotion space and information from online
sources. In audio content analysis we will use music features such as
intensity, timbre and rhythm including their subfeatures to map music in a
2-Dimensional emotional space. In lyric based classification 1-Dimensional
emotional space is used. Both the results are merged onto a 2-Dimensional
emotional space, which will classify song into a particular mood category.
Finally clusters of mood based song files are formed and arranged according to
data acquired from various Internet sources.
