Lyrics-based Analysis and Classification of Music

نویسندگان

  • Michael Fell
  • Caroline Sporleder
چکیده

We present a novel approach for analysing and classifying lyrics, experimenting both with ngram models and more sophisticated features that model different dimensions of a song text, such as vocabulary, style, semantics, orientation towards the world, and song structure. We show that these can be combined with n-gram features to obtain performance gains on three different classification tasks: genre detection, distinguishing the best and the worst songs, and determining the approximate publication time of a song.

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تاریخ انتشار 2014