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http://dx.doi.org/10.14400/JDC.2014.12.10.265

Semantic Ontology Speech Recognition Performance Improvement using ERB Filter  

Lee, Jong-Sub (Dept. of General Education, Semyung University)
Publication Information
Journal of Digital Convergence / v.12, no.10, 2014 , pp. 265-270 More about this Journal
Abstract
Existing speech recognition algorithm have a problem with not distinguish the order of vocabulary, and the voice detection is not the accurate of noise in accordance with recognized environmental changes, and retrieval system, mismatches to user's request are problems because of the various meanings of keywords. In this article, we proposed to event based semantic ontology inference model, and proposed system have a model to extract the speech recognition feature extract using ERB filter. The proposed model was used to evaluate the performance of the train station, train noise. Noise environment of the SNR-10dB, -5dB in the signal was performed to remove the noise. Distortion measure results confirmed the improved performance of 2.17dB, 1.31dB.
Keywords
Information Retrieval; Ontology; Semantic web; ERB;
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Times Cited By KSCI : 2  (Citation Analysis)
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