Adaptive decision fusion for multi-sample speaker verification over GSM networks

Ming Cheung Cheung, Man Wai Mak, Sun Yuan Kung

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)


In speaker verification, a claimant may produce two or more utterances. In our previous study [1], we proposed to compute the optimal weights for fusing the scores of these utterances based on their score distribution and our prior knowledge about the score statistics estimated from the mean scores of the corresponding client speaker and some pseudo-impostors during enrollment. As the fusion weights depend on the prior scores, in this paper, we propose to adapt the prior scores during verification based on the likelihood of the claimant being an impostor. To this end, a pseudo-imposter GMM score model is created for each speaker. During verification, the claimant?s scores are fed to the score model to obtain a likelihood for adapting the prior score. Experimental results based on the GSM-transcoded speech of 150 speakers from the HTIMIT corpus demonstrate that the proposed prior score adaptation approach provides a relative error reduction of 15% when compared with our previous approach where the prior scores are non-adaptive.
Original languageEnglish
Title of host publicationEUROSPEECH 2003 - 8th European Conference on Speech Communication and Technology
PublisherInternational Speech Communication Association
Number of pages4
Publication statusPublished - 1 Jan 2003
Event8th European Conference on Speech Communication and Technology, EUROSPEECH 2003 - Geneva, Switzerland
Duration: 1 Sep 20034 Sep 2003


Conference8th European Conference on Speech Communication and Technology, EUROSPEECH 2003

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Linguistics and Language
  • Communication

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