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http://dx.doi.org/10.9708/jksci.2010.15.1.177

Efficient Continuous Vocabulary Clustering Modeling for Tying Model Recognition Performance Improvement  

Ahn, Chan-Shik (광운대학교 컴퓨터공학과)
Oh, Sang-Yeob (경원대학교 IT대학 컴퓨터미디어학과)
Publication Information
Journal of the Korea Society of Computer and Information / v.15, no.1, 2010 , pp. 177-183 More about this Journal
Abstract
In continuous vocabulary recognition system by statistical method vocabulary recognition to be performed using probability distribution it also modeling using phoneme clustering for based sample probability parameter presume. When vocabulary search that low recognition rate problem happened in express vocabulary result from presumed probability parameter by not defined phoneme and insert phoneme and it has it's bad points of gaussian model the accuracy unsecure for one clustering modeling. To improve suggested probability distribution mixed gaussian model to optimized for based resemble Euclidean and Bhattacharyya distance measurement method mixed clustering modeling that system modeling for be searching phoneme probability model in clustered model. System performance as a result of represent vocabulary dependence recognition rate of 98.63%, vocabulary independence recognition rate of 97.91%.
Keywords
clustering modeling; phoneme modeling; tying model; gaussian model; vocabulary recognition;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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