• DocumentCode
    2976153
  • Title

    Modelling correlation of an ensemble

  • Author

    Smith, F.J. ; Ming, J. ; Hanna, P. ; Stewart, D.

  • Author_Institution
    Sch. of Comput. Sci., Queen´´s Univ., Belfast, UK
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    349
  • Lastpage
    352
  • Abstract
    Two methods have been derived for modelling of uncertain correlation in an ensemble of quantities. One is designed for an unordered ensemble and is valid for Gaussian and non-Gaussian distributions, the second is designed for a Markov sequence, and is valid for a Gaussian distribution. When applied to speech the results for the first method based on an unordered ensemble demonstrate that the traditional assumption in speech that the correlation between frames can be neglected is invalid. The correlation is on average is close to 80% of the maximum possible correlation between the frames. This application demonstrates that this method can be used effectively to solve problems when correlation in an ensemble is important, but is unknown
  • Keywords
    Gaussian distribution; Markov processes; correlation methods; probability; speech processing; Gaussian distributions; Markov sequence; correlation modelling; ensemble; non-Gaussian distribution; speech processing; uncertain correlation; unordered ensemble; Computer science; Equations; Expert systems; Fuzzy logic; Gaussian distribution; Gaussian processes; Pattern recognition; Probability; Speech; US Department of Transportation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Higher-Order Statistics, 1999. Proceedings of the IEEE Signal Processing Workshop on
  • Conference_Location
    Caesarea
  • Print_ISBN
    0-7695-0140-0
  • Type

    conf

  • DOI
    10.1109/HOST.1999.778756
  • Filename
    778756