DocumentCode :
2620789
Title :
HMM-Based Uyghur Continuous Speech Recognition System
Author :
Silamu, Wushour ; Tursun, Nasirjan
Author_Institution :
Sch. of Inf. Sci. & Eng., Xinjiang Univ., Urumqi, China
Volume :
7
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
243
Lastpage :
247
Abstract :
In this work presents a continuous speech recognition system for Uyghur language based on HMM, which called UASRS. Uyghur language is an agglutinative language and one of the least studied languages on speech recognition area. So, our first work was building a Uyghur continuous speech database. In acoustic level, we was using the common used HMM (hidden Markov model) for modeling the Uyghur speech data; in language level, modeling the Uyghur text data based on N-Gram language model. At last we were using the recognizer of HTK3.3 (HMM toolkit) and the MS Visual C + + 8.0 developing the Uyghur continuous speech recognition system. In this paper also presents the recognition experiments of Uyghur continuous speech by using the UASRS. The recognition rate was 68.98% (sentences), and 94.65% (words) for the test set. The recognition rate was 51.49% (sentences), and 85.82% (words) for the real-time speech recognition.
Keywords :
C++ language; audio databases; hidden Markov models; natural languages; speech recognition; HMM; HTK3.3 HMM toolkit; MS Visual C++ language; N-Gram language model; Uyghur continuous speech database; Uyghur continuous speech recognition system; agglutinative language; hidden Markov model; Computer science; Educational institutions; Hidden Markov models; Natural languages; Spatial databases; Speech processing; Speech recognition; Speech synthesis; Stress; Vocabulary; HMM; Uyghur; speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.717
Filename :
5170318
Link To Document :
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