• DocumentCode
    142601
  • Title

    Pitch detection algorithms modifications and implementations towards automated vocal analysis

  • Author

    Yuhong Zhang ; Elkins, Aaron C. ; Nunamaker, Jay F.

  • Author_Institution
    Dept. of Eng. Technol., Texas Southern Univ., Houston, TX, USA
  • fYear
    2014
  • fDate
    7-9 April 2014
  • Firstpage
    405
  • Lastpage
    410
  • Abstract
    Discriminating between deceit and truth is a significant security challenge in a variety of situations, including border crossings, job interviews, flight passenger screenings, and police interviews. Previous research indicates that some features of vocal speech, e.g., fundamental frequency, are related to human emotion and stress levels making them applicable deception detection. This paper focuses on voice and speech feature extraction using advanced signal processing methodology. These generated speech features are used to submit data mining algorithms for classifying deception. The result of this paper is expected to be directly applied to the deception detection system.
  • Keywords
    data mining; feature extraction; signal classification; speech processing; automated vocal analysis; border crossings; data mining algorithms; deception classification; deception detection system; flight passenger screenings; fundamental frequency feature; human emotion; job interviews; pitch detection algorithms; police interviews; security challenge; signal processing methodology; speech feature extraction; speech feature generation; stress levels; vocal speech feature; voice feature extraction; Feature extraction; Speech; deception detection; pitch; speech feature; speech processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control (ICNSC), 2014 IEEE 11th International Conference on
  • Conference_Location
    Miami, FL
  • Type

    conf

  • DOI
    10.1109/ICNSC.2014.6819660
  • Filename
    6819660