Improving PLDA speaker verification using WMFD and linear-weighted approaches in limited microphone data conditions

نویسندگان

  • Ahilan Kanagasundaram
  • David Dean
  • Sridha Sridharan
چکیده

This paper proposes the addition of a weighted median Fisher discriminator (WMFD) projection prior to length-normalised Gaussian probabilistic linear discriminant analysis (GPLDA) modelling in order to compensate the additional session variation. In limited microphone data conditions, a linear-weighted approach is introduced to increase the influence of microphone speech dataset. The linear-weighted WMFD-projected GPLDA system shows improvements in EER and DCF values over the pooled LDAand WMFD-projected GPLDA systems in interview-interview condition as WMFD projection extracts more speaker discriminant information with limited number of sessions/ speaker data, and linear-weighted GPLDA approach estimates reliable model parameters with limited microphone data.

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تاریخ انتشار 2015