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Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music

Please use this identifier to cite or link to this item: http://hdl.handle.net/1811/48548

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Title: Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music
Creators: Hirjee, Hussein; Brown, Daniel
Keywords: song lyrics
phonetic similarity
hip hop
artist classification
Issue Date: 2010-10
Publisher: Empirical Musicology Review
Citation: Empirical Musicology Review, v5 n4 (Oct. 2010), 121-145
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.
Series/Report no.: EMR000091a
ISSN: 1559-5749
Other Identifiers: EMR000091a
URI: http://hdl.handle.net/1811/48548
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