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A Design of Recognition Rate Improving Strategy for Japanese Speech Recognition System

This thesis investigates the recognition rate improvement strategies for a Japanese speech recognition system. Both training data development and consonant correction scheme are studied. For training data development, a database of 995 two-syllable Japanese words is established by phonetic balanced sieving. Furthermore, feature models for the 188 common Japanese mono-syllables are derived through mixed position training scheme to increase recognition rate. For consonant correction, a sub-syllable model is developed to enhance the consonant recognition accuracy, and hence further improve the overall correct rate for the whole Japanese phrases. Experimental results indicate that the average correct rate for Japanese phrase recognition system with 34 thousand phrases can be improved from 86.91% to 92.38%.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0824110-152453
Date24 August 2010
CreatorsLin, Cheng-Hung
ContributorsEr-Hui Lu, Tsung Lee, Xiao-Song Bo, Chih-Chien Chen, Chii-Maw Uang
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0824110-152453
Rightsnot_available, Copyright information available at source archive

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