• DocumentCode
    2364141
  • Title

    Automatic Arabic digit speech recognition and formant analysis for voicing disordered people

  • Author

    Muhammad, Ghulam ; AlMalki, Khalid ; Mesallam, Tamer ; Farahat, Mohamed ; AlSulaiman, Mansour

  • Author_Institution
    Dept. of Comput. Eng., King Saud Univ., Riyadh, Saudi Arabia
  • fYear
    2011
  • fDate
    20-23 March 2011
  • Firstpage
    699
  • Lastpage
    702
  • Abstract
    In this paper, analysis of speech from voice disordered people is performed from automatic speech recognition (ASR) point of view. Six different types of voicing disorder (pathological voice) are analyzed to show the difficulty of automatically recognizing their corresponding speech. As a case study, Arabic spoken digits are taken as input. The distribution of first four formants of vowel /a/ is extracted to show a significant deviation of formants from the normal speech to disordered speech. Experiment result reveals that current ASR technique is far from reliable performance in case of pathological speech, and thereby we need attention to this.
  • Keywords
    diseases; handicapped aids; hearing aids; speech processing; speech recognition; automatic Arabic digit speech recognition; speech formant analysis; voicing disordered people; Accuracy; Diseases; Mel frequency cepstral coefficient; Pathology; Speech; Speech recognition; Training; Arabic digits; formants; speech recognition; voice disorder;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers & Informatics (ISCI), 2011 IEEE Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-61284-689-7
  • Type

    conf

  • DOI
    10.1109/ISCI.2011.5959001
  • Filename
    5959001