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Gedik, Ali Cenk
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01. Izmir Institute of Technology
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6
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3
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5109/4212
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WoS Citation Count
73
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145
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12.17
Scopus Citations per Publication
24.17
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4
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1
| Journal | Count |
|---|---|
| 2009 IEEE 17th Signal Processing and Communications Applications Conference, SIU 2009 | 1 |
| 2011 IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011 | 1 |
| IEEE Transactions on Audio, Speech and Language Processing | 1 |
| Journal of New Music Research | 1 |
| Signal Processing | 1 |
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Now showing 1 - 6 of 6
Article Citation - WoS: 32Citation - Scopus: 61Three 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; 01. Izmir Institute of Technology; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of EngineeringIn 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.Conference Object Citation - Scopus: 6Music Information Retrieval for Turkish Music: Problems, Solutions and Tools(Institute of Electrical and Electronics Engineers Inc., 2009) Bozkurt, Barış; Gedik, Ali Cenk; Karaosmanoğlu, M. Kemal; Bozkurt, Barış; 01. Izmir Institute of Technology; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of EngineeringBu çalışma bilgi erişimi uygulamaları açısından Türk müziğinin Batı müziği ile farklılıklarını tartışmaya açmaktadır. Türk müziği bilgi erişimi için frekans histogramı kullanımını önermekte ve otomatik karar sesi tespiti, makam sınıflandırma, ses sistemi analizi, kuram – icra uyuşma düzeyinin ölçülmesi gibi uygulamalar için geliştirilmiş bir dizi aracı içeren Makam Aracı (Makam Toolbox) 1.0’ın ve beraberinde büyük bir parametrik veritabanının tanıtımını yapmaktadır.Doctoral Thesis Automatic Transcription of Traditional Turkish Art Music Recordings: a Computational Ethnomusicology Appraoach(Izmir Institute of Technology, 2012) Gedik, Ali Cenk; Savacı, Ferit Acar; Gedik, Ali Cenk; Savacı, Ferit Acar; 01. Izmir Institute of Technology; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of EngineeringMusic Information Retrieval (MIR) is a recent research field, as an outcome of the revolutionary change in the distribution of, and access to the music recordings. Although MIR research already covers a wide range of applications, MIR methods are primarily developed for western music. Since the most important dimensions of music are fundamentally different in western and non-western musics, developing MIR methods for non-western musics is a challenging task. On the other hand, the discipline of ethnomusicology supplies some useful insights for the computational studies on nonwestern musics. Therefore, this thesis overcomes this challenging task within the framework of computational ethnomusicology, a new emerging interdisciplinary research domain. As a result, the main contribution of this study is the development of an automatic transcription system for traditional Turkish art music (Turkish music) for the first time in the literature. In order to develop such system for Turkish music, several subjects are also studied for the first time in the literature which constitute other contributions of the thesis: Automatic music transcription problem is considered from the perspective of ethnomusicology, an automatic makam recognition system is developed and the scale theory of Turkish music is evaluated computationally for nine makamlar in order to understand whether it can be used for makam detection. Furthermore, there is a wide geographical region such as Middle-East, North Africa and Asia sharing similarities with Turkish music. Therefore our study would also provide more relevant techniques and methods than the MIR literature for the study of these non-western musics.Article Citation - WoS: 36Citation - Scopus: 64Pitch-Frequency Histogram-Based Music Information Retrieval for Turkish Music(Elsevier Ltd., 2010) Gedik, Ali Cenk; Bozkurt, Barış; Gedik, Ali Cenk; Bozkurt, Barış; 01. Izmir Institute of Technology; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of EngineeringThis 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.Conference Object Citation - Scopus: 6Klasi̇k Türk Müzi̇ği̇ İ̇çin Otomati̇k Notaya Dökme Si̇stemi̇(Institute of Electrical and Electronics Engineers, 2011) Bozkurt, Barış; Bozkurt, Barış; Gedik, Ali Cenk; Gedik, Ali Cenk; Karaosmanoğlu, M. Kemal; 01. Izmir Institute of Technology; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of EngineeringThis study presents an automatic transcription system for Turkish music for the first time in literature. We first discuss the characteristics of Turkish music that are taken into consideration in the design of the system. Then, the following signal processing components of the system are described briefly in relation to each other and explaining their function in the system: f0 estimation, automatic tonic detection and makam recognition based on pitch distributions, frequency and duration quantization. © 2011 IEEE.Article Citation - WoS: 5Citation - Scopus: 8Evaluation of the Makam Scale Theory of Arel for Music Information Retrieval on Traditional Turkish Art Music(Routledge, 2009) Gedik,A.C.; Bozkurt,B.; Bozkurt, Barış; Gedik, Ali Cenk; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyCurrent music information retrieval (MIR) methods are specifically tailored to the needs of western music. Therefore, it is not straightforward to apply these methods to non-western musics such as traditional Turkish art music (TTAM). Western music theory plays a crucial role in MIR studies. The divergence, however, between theory and practice in traditional Turkish art music (TTAM) results in a lack of a reliable theory of TTAM on which MIR techniques can be based. This is particularly true for theories regarding pitch scales and interval structures in TTAM. In this paper, we evaluate the most influential (yet disputable) theory of TTAM, Arel theory, by means of a makam classification task, to understand whether it can provide a basis for MIR studies on TTAM in a similar way western music theory provides a basis for MIR studies on western music. It is shown that Arel theory is overall successful when applied for modality finding in TTAM and that it can be improved if small modifications are introduced following pitch values obtained from musical practice. © 2009, Copyright Taylor & Francis Group, LLC.