An Improved Tibetan Lhasa Speech Recognition Method Based on Deep Neural Network

2017 ◽  
Author(s):  
Wenbin Ruan ◽  
Zhenye Gan ◽  
Bin Liu ◽  
Yin Guo
Keyword(s):  
Neural Network ◽  
Speech Recognition ◽  
Deep Neural Network ◽  
Recognition Method

Rapid Discriminative Learning

2004 ◽  
Vol 8 (2) ◽  
pp. 108-114
Author(s):  
Jun Rokui ◽  
Keyword(s):  
Neural Network ◽  
Speech Recognition ◽  
Hierarchical Model ◽  
Variable Length ◽  
Discriminative Learning ◽  
Learning Method ◽  
Recognition Method ◽  
Highly Effective ◽  
Hierarchical Neural Network

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.

Sign in / Sign up

Export Citation Format

Share Document