Mood Classification of Hindi Songs based on Lyrics

Digitization of music has led to easier access to different forms music across the globe. Increasing work pressure denies the necessary time to listen and evaluate music for a creation of a personal music library. One solution might be developing a music search engine or recommendation system based on different moods. In fact mood label is considered as an emerging metadata in the digital music libraries and online music repositories. In this paper, we proposed mood taxonomy for Hindi songs and prepared a mood annotated lyrics corpus based on this taxonomy. We also annotated lyrics with positive and negative polarity. Instead of adopting a traditional approach to music mood classification based solely on audio features, the present study describes a mood classification system from lyrics as well by combining a wide range of semantic and stylistic features extracted from textual lyrics. We also developed a supervised system to identify the sentiment of the Hindi song lyrics based on the above features. We achieved the maximum average F-measure of 68.30% and 38.49% for classifying the polarities and moods of the Hindi lyrics, respectively.