• DocumentCode
    630410
  • Title

    Robust Vocabulary Recognition Model Using Average Estimator Least Mean Square Filter

  • Author

    Sang-Yeob Oh ; Kyung-Yong Chung

  • Author_Institution
    Dept. of Interactive media, Gachon Univ., Seongnam, South Korea
  • fYear
    2013
  • fDate
    24-26 June 2013
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    Noise estimation and detection algorithm should adopt to a changing environment in a fast manner so they use a LMS filter. However, there are some negative points as well. A LMS filter is very low and it consequently lowers a speech recognition rate. In order to overcome such weak point, I would like to propose a method for the establishment of a robust´ speech recognition model in a noise environment. Since this proposed method allows the cancelation of noise with the AELMS filter in a noise environment, a robust speech recognition model can be established in a noise environment.
  • Keywords
    filtering theory; least mean squares methods; signal denoising; speech recognition; AELMS filter; average estimator least mean square filter; noise cancellation; noise detection algorithm; noise environment; noise estimation algorithm; robust speech recognition model; robust vocabulary recognition model; speech recognition rate; Filtering algorithms; Hidden Markov models; Least squares approximations; Noise; Robustness; Speech; Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Applications (ICISA), 2013 International Conference on
  • Conference_Location
    Suwon
  • Print_ISBN
    978-1-4799-0602-4
  • Type

    conf

  • DOI
    10.1109/ICISA.2013.6579393
  • Filename
    6579393