A Novel Teaching Video Speech Recognition Method Based on HMM Model

Author(s):  
Liuqing Yang
1993 ◽  
Vol 94 (6) ◽  
pp. 3538-3538
Author(s):  
Masafumi Nishimura

Author(s):  
Jun Rokui ◽  

This paper presents MCE/GPD using GPD that is known as a highly effective discriminative learning method. MCE/GPD is an excellent recognition method that is applicable especially to speech recognition, since it excels in recognizing performance and can be used to deal with variable-length vectors. MCE/GPD involves a problem of calculation resulting from c omplicated algorithms making it impractical. In this paper, we propose a learning method to increase speed at learning based on a hierarchical model. We used a hierarchical neural network to evaluate the method’s performance.


2013 ◽  
Vol 717 ◽  
pp. 475-480
Author(s):  
Yang Jie

The language mixing in multi-language speech recognition is one of the hot issues of concern. After analyzing recognition problem, a method to distinguish language with re-class method according to confidence on multi-language recognition result based on Bayesian decision-making rules with minimum error rate and minimum risk was brought out. It can not only avoid cumbersome language recognition in traditional method but also achieve target of decreasing mixing cognition rate. Experiment on Chinese-English mixing recognition shows that the method can distinguish different language and improve speech recognition rate, which has practicality.


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