Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/2760
Title: Pitch-frequency histogram-based music information retrieval for Turkish music
Authors: Gedik, Ali Cenk
Bozkurt, Barış
Keywords: Electronic musical instruments
Automatic makam recognition
Automatic tonic detection
Music information retrieval
Turkish music
Issue Date: Apr-2010
Publisher: Elsevier Ltd.
Source: Gedik, A. C., and Bozkurt, B. (2010). Pitch-frequency histogram-based music information retrieval for Turkish music. Signal Processing, 90(4), 1049-1063. doi:10.1016/j.sigpro.2009.06.017
Abstract: This study reviews the use of pitch histograms in music information retrieval studies for western and non-western music. The problems in applying the pitch-class histogram-based methods developed for western music to non-western music and specifically to Turkish music are discussed in detail. The main problems are the assumptions used to reduce the dimension of the pitch histogram space, such as, mapping to a low and fixed dimensional pitch-class space, the hard-coded use of western music theory, the use of the standard diapason (A4=440 Hz), analysis based on tonality and tempered tuning. We argue that it is more appropriate to use higher dimensional pitch-frequency histograms without such assumptions for Turkish music. We show in two applications, automatic tonic detection and makam recognition, that high dimensional pitch-frequency histogram representations can be successfully used in Music Information Retrieval (MIR) applications without such pre-assumptions, using the data-driven models. © 2009 Elsevier B.V. All rights reserved.
URI: http://doi.org/10.1016/j.sigpro.2009.06.017
http://hdl.handle.net/11147/2760
ISSN: 0165-1684
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File Description SizeFormat 
2760.pdfMakale420.47 kBAdobe PDFThumbnail
View/Open
Show full item record

CORE Recommender

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.