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http://dx.doi.org/10.14400/JDC.2015.13.2.135

Vocabulary Recognition Performance Improvement using k-means Algorithm for GMM Support  

Lee, Jong-Sub (Dept. of General Education, Semyung University)
Publication Information
Journal of Digital Convergence / v.13, no.2, 2015 , pp. 135-140 More about this Journal
Abstract
General CHMM vocabulary recognition system is model observation probability for vocabulary recognition of recognition rate's low. Used as the limiting unit is applied only to some problem in the phoneme model. Also, they have a problem that does not conform to the needs of the search range to meaning of the words in the vocabulary. Performs a phoneme recognition using GMM to improve these problems. We solve the problem according to the limited search words characterized by an improved k-means algorithm. Measure the effectiveness represented by the accuracy and reproducibility as compared to conventional system performance experiments. Performance test results accuracy is 83%p, and recall is 67%p.
Keywords
CHMM(Continuous Hidden Markov Model); GMM(Gaussian Mixture Model); k-means; vocabulary search; vocabulary recognition;
Citations & Related Records
Times Cited By KSCI : 10  (Citation Analysis)
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