Improving PLDA Speaker Verification using WMFD and Linear-weighted Approaches in Limited Microphone Data Conditions

dc.contributor.authorAhilan, K.
dc.contributor.authorDean, D.
dc.contributor.authorSridharan, S.
dc.date.accessioned2021-03-15T07:32:36Z
dc.date.accessioned2022-06-27T10:02:30Z
dc.date.available2021-03-15T07:32:36Z
dc.date.available2022-06-27T10:02:30Z
dc.date.issued2015
dc.description.abstractThis 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 LDA- and 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. Index Terms: speaker verification, i-vectors, GPLDA,WMFD, linear-weighteden_US
dc.identifier.citationKanagasundaram, A., Dean, D., & Sridharan, S. (2015). Improving PLDA speaker verification using WMFD and linear-weighted approaches in limited microphone data conditions. In Sixteenth Annual Conference of the International Speech Communication Association.en_US
dc.identifier.urihttp://repo.lib.jfn.ac.lk/ujrr/handle/123456789/1874
dc.language.isoenen_US
dc.titleImproving PLDA Speaker Verification using WMFD and Linear-weighted Approaches in Limited Microphone Data Conditionsen_US
dc.typeArticleen_US

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