DocumentCode
467811
Title
A Method to Combine HMM and BPNN on Speech Recognition
Author
Wu-Feng ; Chai-Yi
Author_Institution
Inst. of Technol., Taipei
Volume
4
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
1899
Lastpage
1902
Abstract
Applied the concept of phonic state in Hidden Markov Model to construct the input matrix in BP Neural Network as modeling and recognition, which can decrease their dimension (almost to 1/3 - 1/5) under the same recognition rate. On the one hand, it can save much of memory storage space; on the other hand, it would get more efficiency in calculation. In sum, it has good effects in the application need of real time response situation.
Keywords
backpropagation; hidden Markov models; neural nets; speech recognition; BP neural network; Viterbi algorithm; hidden Markov model; phonic state; speech recognition; Cybernetics; Electronic mail; Hidden Markov models; Machine learning; Mechanical engineering; Neural networks; Probability distribution; Space technology; Speech recognition; Viterbi algorithm; BPNN; HMM; HMNM; Recognition rate; Viterbi algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370458
Filename
4370458
Link To Document