Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Institution Author: search.filters.institutionAuthor.Gedik, Ali CenkSubject: search.filters.subject.Music information retrieval

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  • Article
    Citation - WoS: 36
    Citation - Scopus: 64
    Pitch-Frequency Histogram-Based Music Information Retrieval for Turkish Music
    (Elsevier Ltd., 2010) Gedik, Ali Cenk; Bozkurt, Barış
    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.
  • Article
    Citation - WoS: 32
    Citation - Scopus: 61
    Three Dimensions of Pitched Instrument Onset Detection
    (Institute of Electrical and Electronics Engineers Inc., 2010) Holzapfel, Andre; Bozkurt, Barış; Stylianou, Yannis; Gedik, Ali Cenk; Gedik, Ali Cenk; Bozkurt, Barış
    In this paper, we suggest a novel group delay based method for the onset detection of pitched instruments. It is proposed to approach the problem of onset detection by examining three dimensions separately: phase (i.e., group delay), magnitude and pitch. The evaluation of the suggested onset detectors for phase, pitch and magnitude is performed using a new publicly available and fully onset annotated database of monophonic recordings which is balanced in terms of included instruments and onset samples per instrument, while it contains different performance styles. Results show that the accuracy of onset detection depends on the type of instruments as well as on the style of performance. Combining the information contained in the three dimensions by means of a fusion at decision level leads to an improvement of onset detection by about 8% in terms of F-measure, compared to the best single dimension. © 2010 IEEE.