Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
Browse
4 results
Search Results
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.Current 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.Article Citation - WoS: 5Citation - Scopus: 8Usul and Makam Driven Automatic Melodic Segmentation for Turkish Music(Taylor and Francis Ltd., 2014) Bozkurt, Barış; Karaosmanoglu, M. Kemal; Karaçalı, Bilge; Ünal, ErdemAutomatic melodic segmentation is a topic studied extensively, aiming at developing systems that perform grouping of musical events. Here, we consider the problem of automatic segmentation via supervised learning from a dataset containing segmentation labels of an expert. We present a statistical classification-based segmentation system developed specifically for Turkish makam music. The proposed system uses two novel features, a makam-based and an usul-based feature, together with features commonly used in literature. The makam-based feature is defined as the probability of a note to appear at the phrase boundary, computed from the distributions of boundaries with respect to the piece’s makam pitches. Likewise, the usul-based feature is computed from the distributions of boundaries with respect to beats in the rhythmic cycle, usul of the piece. Several experimental setups using different feature groups are designed to test the contribution of the proposed features on three datasets. The results show that the new features carry complementary information to existing features in the literature within the Turkish makam music segmentation context and that the inclusion of new features resulted in statistically significant performance improvement.Article Citation - WoS: 13Citation - Scopus: 20Weighing Diverse Theoretical Models on Turkish Maqam Music Against Pitch Measurements: a Comparison of Peaks Automatically Derived From Frequency Histograms With Proposed Scale Tones(Taylor and Francis Ltd., 2009) Bozkurt, Barış; Yarman, Ozan; Karaosmanoğlu, M. Kemal; Akkoç, CanSince the early 20th century, various theories have been advanced in order to mathematically explain and notate modes of Traditional Turkish music known as maqams. In this article, maqam scales according to various theoretical models based on different tunings are compared with pitch measurements obtained from select recordings of master Turkish performers in order to study their level of match with analysed data. Chosen recordings are subjected to a fully computerized sequence of signal processing algorithms for the automatic determination of the set of relative pitches for each maqam scale: f0 estimation, histogram computation, tonic detection + histogram alignment, and peak picking. For nine well-recognized maqams, automatically derived relative pitches are compared with scale tones defined by theoretical models using quantitative distance measures. We analyse and interpret histogram peaks based on these measures to find the theoretical models most conforming with all the recordings, and hence, with the quotidian performance trends influenced by them.Article Citation - WoS: 25Citation - Scopus: 39An Automatic Pitch Analysis Method for Turkish Maqam Music(Taylor and Francis Ltd., 2008) Bozkurt, BarışAutomatic pitch analysis of large audio databases is essential for studies on music information retrieval and developing a pitch scale theory for Turkish maqam music. However no such study is available. In this article, we first determine the main obstacle as the alignment of frequency analysis results from multiple files. We then propose a new method to automatically detect the tonic of a recording, align the data, and estimate overall frequency histograms from large databases. We show that such histograms can be successfully used for pitch scale (tuning) studies on the recordings of Tanburi Cemil Bey, an undisputed master of the genre
