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文章基本信息

  • 标题:Using Automated Rhyme Detection to Characterize Rhyming Style in Rap Music
  • 本地全文:下载
  • 作者:Brown, Daniel ; Hirjee, Hussein
  • 期刊名称:Empirical Musicology Review
  • 电子版ISSN:1559-5749
  • 出版年度:2010
  • 卷号:5
  • 期号:4
  • 页码:121-145
  • 出版社:Ohio State University Library
  • 摘要: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.
  • 关键词:song lyrics ;phonetic similarity ;rhyme ;hip hop ;artist classification
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