• DocumentCode
    3243803
  • Title

    Automatic visual speech segmentation

  • Author

    Talea, Hamed ; Yaghmaie, Khashayar

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Semnan Univ., Semnan, Iran
  • fYear
    2011
  • fDate
    27-29 May 2011
  • Firstpage
    184
  • Lastpage
    188
  • Abstract
    Speech recognition techniques which rely on audio features of speech degrade in performance in noisy environments. Visual Speech Recognition helps this by incorporating a visual signal into the recognition process. The performance of automatic speech recognition (ASR) system can be significantly enhanced with additional information from visual speech elements such as the movement of lips, tongue, and teeth. This paper introduces a combined method for lip region extraction and mouth area estimation, which is then used to develop technique for automatic visual speech segmentation. The accuracy of this method is verified by applying it for syllable boundary separation and the following vowel segmentation in multi syllable words and phrases.
  • Keywords
    feature extraction; speech recognition; audio features; automatic speech recognition; automatic visual speech segmentation; lip region extraction; mouth area estimation; speech recognition; visual signal; Image segmentation; Noise measurement; Speech; Lip tracking; Speech segmentation; lipreading; visual feature; visual syllable separation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-61284-485-5
  • Type

    conf

  • DOI
    10.1109/ICCSN.2011.6014877
  • Filename
    6014877