Abstract
Uyghur language is an agglutinative language.It is possible to produce a very large number of words from the same root with suffixes,so that the speech recognition of Uyghur language is very difficult.Combined with the characteristics of Uyghur language,this paper built a Uyghur continuous speech database,and designed the Hidden Markov Model(HMM) based Uyghur continuous speech recognition system by using the HTK(HMMToolKit).On the acoustic level,this paper selected triphone as the basic recognition unit,and used many methods such as decision tree,tied-state triphones,fixing the silence models,increasing Gaussian mixture distribution to improve the precision of the models.On the language level,this study used the statistics-based bigram language model.Finally,this paper presented some recognition experiments by using that system.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
