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arXiv · 1206.2484

Architecture for Automated Tagging and Clustering of Song Files According to Mood

Puneet Singh·Ashutosh Kapoor·Vishal Kaushik·Hima Bindu Maringanti
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Abstract

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.

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Puneet Singh, Ashutosh Kapoor, Vishal Kaushik, Hima Bindu Maringanti. 2012-06-12. Architecture for Automated Tagging and Clustering of Song Files According to Mood. https://arxiv.org/abs/1206.2484

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