A proposed decision rule for speaker identification based on a posteriori probability

Dot Tran, Minh Do, Michael Wagner, T. van Le

Research output: Contribution to conferencePaperpeer-review

Abstract

In speaker recognition, the maximum likelihood (ML) rule is used as a criterion to assign a given sequence of acoustic vectors to the maximum likelihood speaker model. However, this rule is not flexible in some cases. An alternative decision rule, the maximum average normalised likelihood (MANL), is proposed in this paper. The theoretical analysis and the experimental results show that the MANL rule can be used in speaker identification and it is more effective than the ML rule in the approaches based on Gaussian mixture model (GMM) and vector quantisation (VQ).

Original languageEnglish (US)
Pages85-88
Number of pages4
StatePublished - 2020
Externally publishedYes
EventWorkshop on Speaker Recognition and its Commercial and Forensic Applications, RLA2C 1998 - Avignon, France
Duration: Apr 20 1998Apr 23 1998

Conference

ConferenceWorkshop on Speaker Recognition and its Commercial and Forensic Applications, RLA2C 1998
CountryFrance
CityAvignon
Period4/20/984/23/98

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing
  • Software

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