• 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