Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs

Jesper Højvang Jensen, Dan P. W. Ellis, Mads Græsbøll Christensen, Søren Holdt Jensen

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

39 Citationer (Scopus)
1190 Downloads (Pure)

Resumé

In music similarity and in the related task of genre classification, a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although the normalized L2 distance was slightly inferior to the Kullback-Leibler distance with respect to classification performance, it has the advantage of obeying the triangle inequality, which allows for efficient searching.
OriginalsprogEngelsk
TitelProceedings of the 8th International Conference on Music Information Retrieval
Antal sider2
ForlagAustrian Computer Society
Publikationsdato2007
Sider107-108
ISBN (Trykt)978-3-85403-218-2
StatusUdgivet - 2007
BegivenhedInternational Conference on Music Information Retrieval - Vienna, Østrig
Varighed: 23 sep. 200727 sep. 2007
Konferencens nummer: 8

Konference

KonferenceInternational Conference on Music Information Retrieval
Nummer8
LandØstrig
ByVienna
Periode23/09/200727/09/2007

Fingerprint

music
evaluation
comparison

Citer dette

Jensen, J. H., Ellis, D. P. W., Christensen, M. G., & Jensen, S. H. (2007). Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs. I Proceedings of the 8th International Conference on Music Information Retrieval (s. 107-108). Austrian Computer Society.
Jensen, Jesper Højvang ; Ellis, Dan P. W. ; Christensen, Mads Græsbøll ; Jensen, Søren Holdt. / Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs. Proceedings of the 8th International Conference on Music Information Retrieval. Austrian Computer Society, 2007. s. 107-108
@inproceedings{0be3b2703f4411dc912d000ea68e967b,
title = "Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs",
abstract = "In music similarity and in the related task of genre classification, a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although the normalized L2 distance was slightly inferior to the Kullback-Leibler distance with respect to classification performance, it has the advantage of obeying the triangle inequality, which allows for efficient searching.",
author = "Jensen, {Jesper H{\o}jvang} and Ellis, {Dan P. W.} and Christensen, {Mads Gr{\ae}sb{\o}ll} and Jensen, {S{\o}ren Holdt}",
year = "2007",
language = "English",
isbn = "978-3-85403-218-2",
pages = "107--108",
booktitle = "Proceedings of the 8th International Conference on Music Information Retrieval",
publisher = "Austrian Computer Society",

}

Jensen, JH, Ellis, DPW, Christensen, MG & Jensen, SH 2007, Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs. i Proceedings of the 8th International Conference on Music Information Retrieval. Austrian Computer Society, s. 107-108, International Conference on Music Information Retrieval, Vienna, Østrig, 23/09/2007.

Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs. / Jensen, Jesper Højvang; Ellis, Dan P. W.; Christensen, Mads Græsbøll; Jensen, Søren Holdt.

Proceedings of the 8th International Conference on Music Information Retrieval. Austrian Computer Society, 2007. s. 107-108.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

T1 - Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs

AU - Jensen, Jesper Højvang

AU - Ellis, Dan P. W.

AU - Christensen, Mads Græsbøll

AU - Jensen, Søren Holdt

PY - 2007

Y1 - 2007

N2 - In music similarity and in the related task of genre classification, a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although the normalized L2 distance was slightly inferior to the Kullback-Leibler distance with respect to classification performance, it has the advantage of obeying the triangle inequality, which allows for efficient searching.

AB - In music similarity and in the related task of genre classification, a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although the normalized L2 distance was slightly inferior to the Kullback-Leibler distance with respect to classification performance, it has the advantage of obeying the triangle inequality, which allows for efficient searching.

M3 - Article in proceeding

SN - 978-3-85403-218-2

SP - 107

EP - 108

BT - Proceedings of the 8th International Conference on Music Information Retrieval

PB - Austrian Computer Society

ER -

Jensen JH, Ellis DPW, Christensen MG, Jensen SH. Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs. I Proceedings of the 8th International Conference on Music Information Retrieval. Austrian Computer Society. 2007. s. 107-108