Empirical Musicology Review (Apr 2011)

Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music

  • Hussein Hirjee,
  • Daniel Brown

DOI
https://doi.org/10.18061/1811/48548
Journal volume & issue
Vol. 5, no. 4
pp. 121 – 145

Abstract

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Imperfect and internal rhymes are two important features in rap music previously ignored in the music information retrieval literature. We developed a method of scoring potential rhymes using a probabilistic model based on phoneme frequencies in rap lyrics. We used this scoring scheme to automatically identify internal and line-final rhymes in song lyrics and demonstrated the performance of this method compared to rules-based models. We then calculated higher-level rhyme features and used them to compare rhyming styles in song lyrics from different genres, and for different rap artists. We found that these detected features corresponded to real- world descriptions of rhyming style and were strongly characteristic of different rappers, resulting in potential applications to style-based comparison, music recommendation, and authorship identification.

Keywords