scholarly journals Semi-Continuous Hidden Markov Model Optimized Pronunciation Pattern Recognition in English Education

2019 ◽  
Vol 17 (S1) ◽  
pp. 1-11
Author(s):  
Ruolin Shi ◽  
Xuebing Zhang ◽  
Rui Chen ◽  
Xinyu Zhang
Keyword(s):  
Pattern Recognition ◽  
Markov Model ◽  
Hidden Markov Model ◽  
English Education ◽  
Hidden Markov

Modified student's t ‐hidden Markov model for pattern recognition and classification

2013 ◽  
Vol 7 (3) ◽  
pp. 219-227 ◽  
Author(s):  
Hui Zhang ◽  
Qing Ming Jonathan Wu ◽  
Thanh Minh Nguyen
Keyword(s):  
Pattern Recognition ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Student’S T

Fuzzy Observable Markov Models for Pattern Recognition

2007 ◽  
Vol 11 (6) ◽  
pp. 662-667
Author(s):  
Dat Tran ◽  
◽  
Wanli Ma ◽  
Dharmendra Sharma
Keyword(s):  
Pattern Recognition ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Vector Quantization ◽  
Markov Models ◽  
Hidden Markov ◽  
Gaussian Mixture ◽  
Written Language ◽  
Mathematical Framework ◽  
Fuzzy Observable

This paper presents a mathematical framework for fuzzy discrete and continuous observable Markov models (OMMs) and their applications to written language, spam email and typist recognition. Experimental results show that the proposed OMMs are more effective than models such as vector quantization, Gaussian mixture model and hidden Markov model.

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