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Revisiting A Trend Analysis on Concreteness of Popular Song Lyrics
  返回威尼斯人平台主页   发布时间:2019-12-23   发布人:    浏览次数:341

 

报告题目:Revisiting A Trend Analysis on Concreteness of Popular Song Lyrics

  





人:Prof. Dr. J. Stephen Downie


          GSLIS, University of Illinois at Urbana-Champaign, USA                

叶鹰   教授 (Prof. Dr. Fred Y. Ye)

报告时间:202016日(星期一)上午930-1030

报告地点:威尼斯人平台A211会议室

报告摘要:

This talk represents the work premiered by Co-Author Dr. Kayhun Choi at the 2019 Digital Libraries for Musiclogy meeting in The Hague.  Recently, music complexity has drawn attention from researchers in Music Digital Libraries area. In particular, computational methods to measure music complexity have been studied to provide better music services in large-scale music digital libraries. However, the majority of music complexity research has focused on audio-related facets of music, while song lyrics have been rarely considered. Based on the observation that most popular songs contain lyrics, whose different levels of complexity contribute to the overall music complexity, this paper investigates song lyric complexity and how it might be measured computationally. In particular, this paper examines the concreteness of song lyrics using trend analysis. Our analysis on the popular songs indicates that concreteness of popular song lyrics fell from the middle of the 1960s until the 1990s and rose after that. The advent of Hip-Hop/Rap and the number of words in song lyrics are highly correlated with the rise in concreteness after the early 1990s.

报告人介绍:

J. Stephen Downie is the Associate Dean for Research and a Professor at the School of Information Sciences at the University of Illinois at Urbana-Champaign. Dr. Downie is the Illinois Co-Director of the HathiTrust Research Center (HTRC). Downie is the leader of the Hathitrust + Bookworm (HT+BW) text analysis project that is creating tools to visualize the evolution of term usage over time. Professor Downie represents the HTRC on the NOVEL(TM) text mining project and the Single Interface for Music Score Searching and Analysis (SIMSSA) project, both funded by the SSHRC Partnership Grant programme. All of these aforementioned projects share a common thread of striving to provide large-scale analytic access to copyright-restricted cultural data. Dr. Downie has been very active in the establishment of the Music Information Retrieval (MIR) community through his ongoing work with the International Society for Music Information Retrieval (ISMIR) conferences. He was ISMIR's founding President and recently served on the ISMIR board. Several years ago, Professor Downie worked with Dunhuang Academy on the Digital Dunhuang project to help connect Digital Humanities scholars with the high-resolution digital materials capturing the Mogao Caves. Professor Downie holds a BA (Music Theory and Composition) along with a Master's and a PhD in Library and Information Science, all earned at the University of Western Ontario, London, Canada.

 

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