TY - GEN
T1 - Music structure segmentation algorithm evaluation
T2 - 12th International Society for Music Information Retrieval Conference, ISMIR 2011
AU - Ehmann, Andreas F.
AU - Bay, Mert
AU - Downie, J. Stephen
AU - Fujinaga, Ichiro
AU - De Roure, David
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84873605778&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84873605778&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84873605778
SN - 9780615548654
T3 - Proceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011
SP - 561
EP - 566
BT - Proceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011
Y2 - 24 October 2011 through 28 October 2011
ER -