Müzik türlerinin siniflandirilmasinda benzer kesişim bilgileri uygulamalari

Ulaş Baǧci; Engin Erzin

doi:10.1109/SIU.2006.1659788

Müzik türlerinin siniflandirilmasinda benzer kesişim bilgileri uygulamalari

Translated title of the contribution: Inter genre similarity modeling for automatic music genre classification

Ulaş Baǧci^*, Engin Erzin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modeling (IGS) to improve the automatic music genre classification performance. Intergenre similarity information is extracted over the mis-classified feature population. Once the inter-genre similarity is modeled, elimination of the inter-genre similarity reduces the inter-genre confusion and improves the identification rates. Inter-genre similarity modeling is further improved with iterative IGS modeling and score modeling for IGS elimination. Experimental results with promising classification improvements are provided.

Translated title of the contribution	Inter genre similarity modeling for automatic music genre classification
Original language	Turkish
Title of host publication	2006 IEEE 14th Signal Processing and Communications Applications Conference
DOIs	https://doi.org/10.1109/SIU.2006.1659788
State	Published - 2006
Externally published	Yes
Event	2006 IEEE 14th Signal Processing and Communications Applications - Antalya, Turkey Duration: Apr 17 2006 → Apr 19 2006

Publication series

Name	2006 IEEE 14th Signal Processing and Communications Applications Conference
Volume	2006

Conference

Conference	2006 IEEE 14th Signal Processing and Communications Applications
Country/Territory	Turkey
City	Antalya
Period	4/17/06 → 4/19/06

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing
Electrical and Electronic Engineering

Access to Document

10.1109/SIU.2006.1659788

Cite this

@inproceedings{e6c3fc26a0f14020b153ff7d73d85d9a,

title = "M{\"u}zik t{\"u}rlerinin siniflandirilmasinda benzer kesi{\c s}im bilgileri uygulamalari",

abstract = "Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modeling (IGS) to improve the automatic music genre classification performance. Intergenre similarity information is extracted over the mis-classified feature population. Once the inter-genre similarity is modeled, elimination of the inter-genre similarity reduces the inter-genre confusion and improves the identification rates. Inter-genre similarity modeling is further improved with iterative IGS modeling and score modeling for IGS elimination. Experimental results with promising classification improvements are provided.",

author = "Ula{\c s} Baǧci and Engin Erzin",

year = "2006",

doi = "10.1109/SIU.2006.1659788",

language = "Turkish",

isbn = "1424402395",

series = "2006 IEEE 14th Signal Processing and Communications Applications Conference",

booktitle = "2006 IEEE 14th Signal Processing and Communications Applications Conference",

}

Baǧci, U & Erzin, E 2006, Müzik türlerinin siniflandirilmasinda benzer kesişim bilgileri uygulamalari. in 2006 IEEE 14th Signal Processing and Communications Applications Conference., 1659788, 2006 IEEE 14th Signal Processing and Communications Applications Conference, vol. 2006, 2006 IEEE 14th Signal Processing and Communications Applications, Antalya, Turkey, 4/17/06. https://doi.org/10.1109/SIU.2006.1659788

Müzik türlerinin siniflandirilmasinda benzer kesişim bilgileri uygulamalari. / Baǧci, Ulaş; Erzin, Engin.
2006 IEEE 14th Signal Processing and Communications Applications Conference. 2006. 1659788 (2006 IEEE 14th Signal Processing and Communications Applications Conference; Vol. 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Müzik türlerinin siniflandirilmasinda benzer kesişim bilgileri uygulamalari

AU - Baǧci, Ulaş

AU - Erzin, Engin

PY - 2006

Y1 - 2006

N2 - Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modeling (IGS) to improve the automatic music genre classification performance. Intergenre similarity information is extracted over the mis-classified feature population. Once the inter-genre similarity is modeled, elimination of the inter-genre similarity reduces the inter-genre confusion and improves the identification rates. Inter-genre similarity modeling is further improved with iterative IGS modeling and score modeling for IGS elimination. Experimental results with promising classification improvements are provided.

AB - Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modeling (IGS) to improve the automatic music genre classification performance. Intergenre similarity information is extracted over the mis-classified feature population. Once the inter-genre similarity is modeled, elimination of the inter-genre similarity reduces the inter-genre confusion and improves the identification rates. Inter-genre similarity modeling is further improved with iterative IGS modeling and score modeling for IGS elimination. Experimental results with promising classification improvements are provided.

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U2 - 10.1109/SIU.2006.1659788

DO - 10.1109/SIU.2006.1659788

M3 - Conference contribution

AN - SCOPUS:34247123635

SN - 1424402395

SN - 9781424402397

T3 - 2006 IEEE 14th Signal Processing and Communications Applications Conference

BT - 2006 IEEE 14th Signal Processing and Communications Applications Conference

T2 - 2006 IEEE 14th Signal Processing and Communications Applications

Y2 - 17 April 2006 through 19 April 2006

ER -

Müzik türlerinin siniflandirilmasinda benzer kesişim bilgileri uygulamalari

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

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