Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music

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dc.creator Hirjee, Hussein
dc.creator Brown, Daniel 2011-04-25T14:56:21Z 2011-04-25T14:56:21Z 2010-10
dc.identifier.citation Empirical Musicology Review, v5 n4 (Oct. 2010), 121-145 en_US
dc.identifier.issn 1559-5749
dc.identifier.other EMR000091a
dc.description.abstract 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. en_US
dc.language.iso en en_US
dc.publisher Empirical Musicology Review en_US
dc.relation.ispartofseries EMR000091a en_US
dc.subject song lyrics en_US
dc.subject phonetic similarity en_US
dc.subject rhyme en_US
dc.subject hip hop en_US
dc.subject artist classification en_US
dc.title Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music en_US
dc.type Article en_US