Music structure segmentation algorithm evaluation: Expanding on MIREX 2010 analyses and datasets

Andreas F. Ehmann, Mert Bay, J. Stephen Downie, Ichiro Fujinaga, David De Roure

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Music audio structure segmentation has been a task in the Music Information Retrieval Evaluation eXchange (MIREX) since 2009. In 2010, five algorithms were evaluated against two datasets (297 and 100 songs) with an almost exclusive focus on western popular music. A new annotated dataset significantly larger in size and with a more diverse range of musical styles became available in 2011. This new dataset comprises over 1,300 songs spanning pop, jazz, classical, and world music styles. The algorithms from the 2010 iteration of MIREX are re-evaluated against this new dataset. This paper presents a detailed analysis of these evaluation results in order to gain a better understanding of the current state-of-the-art in automatic structure segmentation. These expanded analyses focus on the interaction of algorithm performance and rankings with datasets, musical styles, and annotation level. Because the new dataset contains multiple annotations for each song, we also introduce a baseline for expected human performance for this task.

Original languageEnglish (US)
Title of host publicationProceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011
Pages561-566
Number of pages6
StatePublished - 2011
Event12th International Society for Music Information Retrieval Conference, ISMIR 2011 - Miami, FL, United States
Duration: Oct 24 2011Oct 28 2011

Publication series

NameProceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011

Other

Other12th International Society for Music Information Retrieval Conference, ISMIR 2011
Country/TerritoryUnited States
CityMiami, FL
Period10/24/1110/28/11

ASJC Scopus subject areas

  • Music
  • Information Systems

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