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Erschienen in:
2003 | OriginalPaper | Buchkapitel
Parameter Optimization by a Genetic Algorithm for a Pitch Tracking System
verfasst von : Yoon-Seok Choi, Byung-Ro Moon
Erschienen in: Genetic and Evolutionary Computation — GECCO 2003
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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The emergence of multimedia data in databases requires adequate methods for information retrieval. In a music data retrieval system by humming, the first stage is to extract exact pitch periods from a flow of signals. Due to the complexity of speech signals, it is difficult to make a robust and practical pitch tracking system. We adopt genetic algorithm in optimizing the control parameters for note segmentation and pitch determination. We applied the results to HumSearch, a commercialized product, as a pitch tracking engine. Experimental results showed that the proposed engine notably improved the performance of the existing engine in HumSearch.