• DocumentCode
    242924
  • Title

    Application of neuro-fuzzy approaches to recognition and classification of infant cry

  • Author

    Srijiranon, Krittakom ; Eiamkanitchat, Narissara

  • Author_Institution
    Dept. of Comput. Eng., Chiang Mai Univ., Chiang Mai, Thailand
  • fYear
    2014
  • fDate
    22-25 Oct. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Languages are used as a tool for human to communicate their needs to one another. To be able to use any language human beings need time to learn to achieve understanding. The newborn babies use their cries by their instinct to communicate their needs. The difference cries of the infant can indicate different requirements. This work proposes a method to determine the meanings of infant cries according to the baby expert. It applies the novel Neuro-fuzzy techniques for the classification and Perceptual Linear Prediction for recognition the infant cries. The results showed that the classification performance obtained by using the Neuro-fuzzy yielded the most desirable accuracy than others popular methods. In addition, The Neuro-fuzzy structure designed in this paper can be applied to speech recognition of other further research.
  • Keywords
    fuzzy neural nets; signal classification; speech recognition; classification performance; infant cry classification; infant cry recognition; neuro-fuzzy approach; perceptual linear prediction; speech recognition; Accuracy; Classification algorithms; Feature extraction; Mel frequency cepstral coefficient; Neural networks; Speech recognition; Support vector machine classification; Infant cry classification; Neuro-Fuzzy; Perceptual Linear Prediction (PLP);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2014 - 2014 IEEE Region 10 Conference
  • Conference_Location
    Bangkok
  • ISSN
    2159-3442
  • Print_ISBN
    978-1-4799-4076-9
  • Type

    conf

  • DOI
    10.1109/TENCON.2014.7022296
  • Filename
    7022296