Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

Browse

Filters

2008 - 200922010 - 20152

Settings

Author: search.filters.author.Bozkurt, BarışWoS Q: search.filters.wosQuartile.Q4

Search Results

Now showing 1 - 4 of 4
  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    A Computational Analysis of Turkish Makam Music Based on a Probabilistic Characterization of Segmented Phrases
    (Taylor and Francis Ltd., 2015) Bozkurt, Barış; Karaçalı, Bilge
    This study targets automatic analysis of Turkish makam music pieces on the phrase level. While makam is most simply defined as an organization of melodic phrases, there has been very little effort to computationally study melodic structure in makam music pieces. In this work, we propose an automatic analysis algorithm that takes as input symbolic data in the form of machine-readable scores that are segmented into phrases. Using a measure of makam membership for phrases, our method outputs for each phrase the most likely makam the phrase comes from. The proposed makam membership definition is based on Bayesian classification and the algorithm is specifically designed to process the data with overlapping classes. The proposed analysis system is trained and tested on a large data set of phrases obtained by transferring phrase boundaries manually written by experts of makam music on printed scores, to machine-readable data. For the task of classifying all phrases, or only the beginning phrases to come from the main makam of the piece, the corresponding F-measures are.52 and.60 respectively.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 8
    Usul and Makam Driven Automatic Melodic Segmentation for Turkish Music
    (Taylor and Francis Ltd., 2014) Bozkurt, Barış; Karaosmanoglu, M. Kemal; Karaçalı, Bilge; Ünal, Erdem
    Automatic 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: 13
    Citation - Scopus: 20
    Weighing 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, Can
    Since 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: 25
    Citation - Scopus: 39
    An Automatic Pitch Analysis Method for Turkish Maqam Music
    (Taylor and Francis Ltd., 2008) Bozkurt, Barış
    Automatic 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