• DocumentCode
    706267
  • Title

    Screening for high risk suicidal states using mel-cepstral coefficients and energy in frequency bands

  • Author

    Keskinpala, Hande Kaymaz ; Yingthawornsuk, Thaweesak ; Wilkes, D. Mitch ; Shiavi, Richard G. ; Salomon, Ronald M.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Vanderbilt Univ., Nashville, TN, USA
  • fYear
    2007
  • fDate
    3-7 Sept. 2007
  • Firstpage
    2229
  • Lastpage
    2233
  • Abstract
    Distinguishing high risk suicidal patients from less severely depressed patients at low risk is a critical problem. This paper describes a novel way to address this issue. The vocal characteristics of male and female speech samples from high risk suicidal and depressed patients were analyzed and distinguished using mel-cepstral coefficients and using energy in frequency bands. Two kinds of speech samples, one from an interview session and the other from a reading session, were analyzed. The results show that mel-cepstral coefficients and energy in frequency bands may be used to separate these populations and the controlled reading tended to provide better results than the interview.
  • Keywords
    adaptive signal processing; blind source separation; cepstral analysis; medical signal processing; speech; speech processing; speech recognition; depressed patient vocal characteristic analysis; female speech sample vocal characteristics; frequency band energy; high risk suicidal patient; high risk suicidal state; interview session-derived speech sample; less severely depressed patient; low risk suicidal patient; mel-cepstral coefficient; reading session-derived speech sample; speech sample analysis; suicidal patient identification; suicidal patient vocal characteristics analysis; suicidal state screening; Cepstral analysis; Databases; Feature extraction; Interviews; Speech; Speech processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2007 15th European
  • Conference_Location
    Poznan
  • Print_ISBN
    978-839-2134-04-6
  • Type

    conf

  • Filename
    7099204