OSU Navigation Bar

The Ohio State University University Libraries Knowledge Bank

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

Show full item record

Files Size Format View
EMR000091a-Hirjee_Brown.pdf 442.5Kb PDF View/Open

Title: Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music
Creators: Hirjee, Hussein; Brown, Daniel
Keywords: song lyrics
phonetic similarity
rhyme
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
Bookmark and Share