Popular music representation: chorus detection & emotion recognition

Chia Hung Yeh, Wen Yu Tseng, Chia Yen Chen*, Yu Dun Lin, Yi Ren Tsai, Hsuan I. Bi, Yu Ching Lin, Ho Yi Lin

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

9 引文 斯高帕斯(Scopus)

摘要

This paper proposes a popular music representation strategy based on the song’s emotion. First, a piece of popular music is decomposed into chorus and verse segments through the proposed chorus detection algorithm. Three descriptive features: intensity, frequency band and rhythm regularity are extracted from the structured segments for emotion detection. A hierarchical Adaboost classifier is employed to recognize the emotion of a piece of popular music. The general emotion of the music is classified according to Thayer’s model into four emotions: happy, angry, depressed and relaxed. Experiments conducted on a 350-popular-music database show the average recall and precision of our proposed chorus detection are approximately 95 % and 84 %, respectively; and the average precision rate of emotion detection is 92 %. Additional tests are performed on songs with cover versions in different lyrics and languages, and the resultant precision rate is 90 %. The proposes approaches have been tested and proven by the professional online music company, KKBOX Inc. and show promising performance for effectively and efficiently identifying the emotions of a variety of popular music.

原文英語
頁(從 - 到)2103-2128
頁數26
期刊Multimedia Tools and Applications
73
發行號3
DOIs
出版狀態已發佈 - 2014 十月 29
對外發佈

ASJC Scopus subject areas

  • 軟體
  • 媒體技術
  • 硬體和架構
  • 電腦網路與通信

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