Deriving Music Theme Annotations from User Tags

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Abstract

Music theme annotations would be really beneficial for supporting retrieval, but are often neglected by users while annotating. Thus, in order to support users in tagging and to fill the gaps in the tag space, in this paper we develop algorithms for recommending theme annotations. Our methods exploit already existing user tags, the lyrics of music tracks, as well as combinations of both. We compare the results for our recommended theme annotations against genre and style recommendations – a much easier and already studied task. We evaluate the quality of our recommended tags against an expert ground truth data set. Our results are promising and provide interesting insights into possible extensions for music tagging systems to support music search.