DocumentCode
1798204
Title
A novel intelligent system for speech recognition
Author
Silva, Washington Luis Santos ; de Oliveira Serra, Ginalber Luiz
Author_Institution
Dept. of Electroelectronics, Fed. Inst. of Educ., Sao Luis, Brazil
fYear
2014
fDate
6-11 July 2014
Firstpage
3599
Lastpage
3604
Abstract
The concept of fuzzy sets and fuzzy logic is widely used to propose several methods applied to modeling, classification and pattern recognition problem. This paper proposes an Intelligent Methodology for Speech Recognition (IMSR). In addition to pre-processing, with mel-cepstral coefficients, the Discrete Cosine Transform (DCT) is used to generate a two-dimensional time matrix for each pattern to be recognized. A genetic algorithm is used to optimize a Mamdani fuzzy inference system in order to obtain the best model with minimum number of parameters for final recognition. Experimental results for speech recognition applied to Brazilian language show the efficiency of the proposed methodology compared to methodologies widely used and cited in the literature.
Keywords
cepstral analysis; discrete cosine transforms; fuzzy logic; fuzzy reasoning; fuzzy set theory; genetic algorithms; matrix algebra; natural language processing; speech recognition; Brazilian language; DCT; IMSR; Mamdani fuzzy inference system; discrete cosine transform; fuzzy logic; fuzzy sets; genetic algorithm; intelligent methodology for speech recognition; intelligent system; mel-cepstral coefficient; pattern recognition; two-dimensional time matrix; Discrete cosine transforms; Fuzzy logic; Genetic algorithms; Hidden Markov models; Speech; Speech recognition; Training; Automatic Speech Recognition; Discrete Cosine Transform; Fuzzy Systems; Genetic Algorithms; Instelligent System;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6627-1
Type
conf
DOI
10.1109/IJCNN.2014.6889833
Filename
6889833
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