Attractive Phrase Detection from Musical Lyric Focusing on Linguistic Expressions

Ryosuke Yamanishi
College of Information Science and Engineering, Ritsumeikan University, Japan

Risako Kagita
College of Information Science and Engineering, Ritsumeikan University, Japan

Yoko Nishihara
College of Information Science and Engineering, Ritsumeikan University, Japan

Junichi Fukumoto
College of Information Science and Engineering, Ritsumeikan University, Japan

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Ingår i: KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13

Linköping Electronic Conference Proceedings 100:121, s. 1453-1463

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Publicerad: 2014-06-11

ISBN: 978-91-7519-276-5

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


This paper describes a method for extracting attractive phrases of lyric focusing on linguistic expressions. Not only chorus but also linguistic expressions seem to be a cause of attractive phrases. We conducted impressive evaluation experiments to clarify the important factors of attraction of phrase. As the result; it was confirmed that “uniqueness of co-occurred terms” and “repetition” especially influenced attraction. Therefore; we modeled the uniqueness of co-occurred terms and repetition as seven mathematical features. And the proposed method detected attractive phrases using support vector machine with the modeled features; which is known as a high performance pattern recognition method. Through the attractive phrase detection experiments; we confirmed availability of the proposed method: the accuracy level and the precision was each 69% and 86%; respectively. Moreover; we discussed about the correctly detected attractive phrases comparing key sentences detected by the existing summarization methods. As the result of the discussions; the proposed method correctly detected the phrases that were ranked in low by the conventional methods though human evaluated the phrases as attractive. From these facts; it was suggested that lyrical linguistic expressions were well modeled in the proposed method; and the proposed method detected the attractive phrases better than the existing summarization method.


Music; Lyric; Attractive Phrase; Natural Language Processing


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