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Bozkurt, Barış

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Barış

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Bozkurt

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Bozkurt, Barış

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2014 - 20164

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Researcher Of Publications: search.filters.isAuthorOfPublication.905f4c58-2f2a-49be-a217-e60b97bb20a8

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    Fundamental frequency estimation for heterophonical Turkish music by using VMD
    (Institute of Electrical and Electronics Engineers (IEEE), 2016) Simsek, Berrak Ozturk; Akan, Aydin; Department of Computer Engineering; Bozkurt, Barış; Faculty Member; Department of Computer Engineering; College of Engineering; N/A
    In this study, a new method is presented for the fundamental frequency estimation of heterophonical Turkish makam music recordings that include percusssive instrument by using Variational Mode Decomposition (VMD). VMD is a method to decompose an input signal into an ensemble of sub-signals (modes) which is entirely non-recursive and determines the relevant bands adaptively and estimates the corresponding modes concurrently. In order to decompose a given signal optimally, actuated by the narrow-band properties corresponding to the Intrinsic Mode Function definition used in Emprical Mode Decomposition (EMD), and we seek an ensemble of modes. Simulation results on fundamental frequency estimation of real music data show comparable performance to other common decomposition methods for music signals such as YIN and MELODIA based methods.
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    Automatic tonic identification method for Turkish makam music
    (IEEE, 2015) Atlı, Hasan Sercan; Department of Computer Engineering; Bozkurt, Barış; Faculty Member; Department of Computer Engineering; College of Engineering; N/A
    Tonic is a fundamental concept in makam. As in many world music cultures, tonic frequency varies among performances. Because of this, correct estimation of tonic frequency is important for other computational research problems like tuning analysis, audio-score alignment, automatic transcription etc. In this work, we present a new methodology for automatic tonic estimation of Turkish makam music recordings. New methodology bases on the frequency estimation of the last note in a performance./ Öz: Automatic tonic identification method for Turkish makam music
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    A corpus for computational research of Turkish makam music
    (Association for Computing Machinery, 2014) Uyar, Burak; Atli, Hasan Sercan; Şentürk, Sertan; Serra, Xavier; Department of Computer Engineering; Bozkurt, Barış; Faculty Member; Department of Computer Engineering; College of Engineering; N/A
    Each music tradition has its own characteristics in terms of melodic, rhythmic and timbral properties as well as semantic understandings. To analyse, discover and explore these culture-specific characteristics, we need music collections which are representative of the studied aspects of the music tradition. For Turkish makam music, there are various resources available such as audio recordings, music scores, lyrics and Editorial material metadata. However, most of these resources are not typically suited for computational analysis, are hard to access, do not have sufficient quality or do not include adequate descriptive information. In this paper we present a corpus of Turkish makam music created within the scope of the CompMusic project. The corpus is intended for computational research and the primary considerations during the creation of the corpus reflect some criteria, namely, purpose, coverage, completeness, quality and re-usability. So far, we have gathered approximately 6000 audio recordings, 2200 music scores with lyrics and 27000 instances of Editorial material metadata related to Turkish makam music. The metadata include information about makams, recordings, scores, compositions, artists etc. as well as the interrelations between them. In this paper, we also present several test datasets of Turkish makam music. Test datasets contain manual annotations by experts and they provide ground truth for specific computational tasks to test, calibrate and improve the research tools. We hope that this research corpus and the test datasets will facilitate academic studies in several fields such as music information retrieval and computational musicology.
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    Fundamental frequency estimation for monophonical Turkish music by using VMD
    (IEEE, 2015) Şimşek, Berrak Öztürk; Akan, Aydın; Department of Computer Engineering; Bozkurt, Barış; Faculty Member; Department of Computer Engineering; College of Engineering; N/A
    In this study, a new method is presented for the fundamental frequency estimation of Turkish makam music recordings by using Variational Mode Decomposition (VMD). VMD is a method to decompose an input signal into an ensemble of sub-signals (modes) which is entirely non-recursive and determines the relevant bands adaptively and estimates the corresponding modes concurrently. In order to decompose a given signal optimally, actuated by the narrow-band properties corresponding to the Intrinsic Mode Function (IMF) definition used in Emprical Mode Decomposition (EMD), and we seek an ensemble of modes. Simulation results on fundamental frequency estimation of real music and synthetic test data show better performance compared to other common decomposition methods for music signals such as spectrogram, YIN, MELODIA and EMD based methods.