Paper data
Title:
Recognition of Isolated Musical Patterns using Context Dependent Dynamic Time Warping Author(s): Pikrakis Aggelos, Dept. of Informatics and Telecommunications, University of Athens, Panepistimioupolis, Ilisia 15784, Theodoridis Sergios, Dept. of Informatics and Telecommunications, University of Athens, Panepistimioupolis, Ilisia 15784, Kamarotos Dimitris, IPSA Institute of the Aristotle University of Thessaloniki Page numbers in the proceedings: Volume III pp 129-132 Session: Multimedia Data Protection / Speech Analysis and Recognition
Paper abstract
This paper presents an efficient method for recognizing isolated musical patterns in a monophonic environment, using a novel extension of Dynamic Time Warping, which we call Context Dependent Dynamic Time Warping. Each pattern is converted into a sequence of frequency jumps by means of a fundamental frequency tracking algorithm, followed by a quantizer. The resulting sequence of frequency jumps is presented to the input of the recognizer which employs Context Dependent Dynamic Time Warping. The main characteristic of Context Dependent Dynamic Time Warping is that it exploits the correlation exhibited among adjacent frequency jumps of the feature sequence. The methodology has been tested in the context of Greek Traditional Music, which exhibits certain characteristics that make the classification task harder, when compared with Western musical tradition. A recognition rate higher than 95% was achieved.
Paper
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