淡江大學機構典藏:Item 987654321/70619
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    Title: Distributed fuzzy rules for preprocessing of speech segmentation with genetic algorithm
    Other Titles: 利用遺傳演算法以分散式模糊規則為基礎的語音切割的前處理
    Authors: Hsieh, Ching-tang;Lai, Eugene;Wang, You-chuang
    Contributors: 淡江大學電機工程學系
    Date: 1997-07-01
    Issue Date: 2011-10-23 21:30:18 (UTC+8)
    Publisher: IEEE Neural Networks Council; Artificial Intelligence Research Institute of the CSIC
    Abstract: Most of the speech segmentation works are based on the thresholds of parameters to segment the speech data into phonemic units or syllabic units. In this paper, we formulate the threshold decision as a clustering problem. Feature parameters extracted from the analysis frame are clustered into three types: silence, consonants, and vowels. Distributed fuzzy rules which have been used in clustering the numerical data are used for this task. The distributed fuzzy rules, which do not need many training data, have good performance in clustering problems and are beneficial for clustering the features of speech data. Such a method, however, has many fuzzy if-then rules. So, we propose a genetic-algorithm-based method for selecting a small number of significant fuzzy if-then rules to construct a compact fuzzy classification system with high classification power. Effectiveness of this approach has been substantiated by classification experiments for continuous radio news speech samples uttered by two females and two males
    Relation: Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on vol.1, pp.427-431
    DOI: 10.1109/FUZZY.1997.616406
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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