Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

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

Browse

Filters

2005 - 20094

Settings

End date: 2009Subject: search.filters.subject.Signal processing

Search Results

Now showing 1 - 4 of 4
  • 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
  • Conference Object
    Citation - Scopus: 5
    Musical Note and Instrument Classification With Likelihood-Frequency Analysis and Support Vector Machines
    (Institute of Electrical and Electronics Engineers Inc., 2007) Özbek, Mehmet Erdal; Delpha, Claude; Duhamel, Pierre
    In this paper, we analyze the classification performance of a likelihood-frequency-time (LiFT) analysis designed for partial tracking and automatic transcription of music using support vector machines. The LiFT analysis is based on constant-Q filtering of signals with a filter-bank designed to filter 24 quarter-tone frequencies of an octave. Using the LiFT information, features are extracted from the isolated note samples and classification of instruments and notes is performed with linear, polynomial and radial basis function kernels. Correct classification ratios are obtained for 19 instrument and 36 notes.
  • Conference Object
    Approximate Best Linear Unbiased Channel Estimation for Frequency Selective Channels With Long Delay Spreads: Robustness To Timing and Carrier Offsets
    (Institute of Electrical and Electronics Engineers Inc., 2005) Özen, Serdar; Nerayanuru, Sreenivasa M.; Pladdy, Christopher; Fimoff, Mark J.
    We provide an iterative and a non-iterative channel impulse response (CIR) estimation algorithm for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols. The iterative procedure calculates the (semi-blind) Best Linear Unbiased Estimate (BLUE) of the CIR. The non-iterative version is an approximation to the BLUE CIR estimate, denoted by a-BLUE, achieving almost similar performance, with much lower complexity. Indeed we show that, with reasonable assumptions, a-BLUE channel estimate can be obtained by using a stored copy of a pre-computed matrix in the receiver which enables the use of the initial CIR estimate by the subsequent equalizer tap weight calculator. Simulation results are provided to demonstrate the performance of the novel algorithms for 8-VSB ATSC Digital TV system. We also provide a simulation study of the robustness of the a-BLUE algorithm to timing and carrier phase offsets.