Improving short utterance i-vector speaker verification using utterance variance modelling and compensation techniques

Kanagasundaram, A., Dean, D., Sridharan, S., Gonzalez-Dominguez, J., Gonzalez-Rodriguez, J., & Ramos, D. (2014) Improving short utterance i-vector speaker verification using utterance variance modelling and compensation techniques. Speech Communication, 59, pp. 69-82.

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This paper proposes techniques to improve the performance of i-vector based speaker verification systems when only short utterances are available. Short-length utterance i-vectors vary with speaker, session variations, and the phonetic content of the utterance. Well established methods such as linear discriminant analysis (LDA), source-normalized LDA (SN-LDA) and within-class covariance normalisation (WCCN) exist for compensating the session variation but we have identified the variability introduced by phonetic content due to utterance variation as an additional source of degradation when short-duration utterances are used. To compensate for utterance variations in short i-vector speaker verification systems using cosine similarity scoring (CSS), we have introduced a short utterance variance normalization (SUVN) technique and a short utterance variance (SUV) modelling approach at the i-vector feature level. A combination of SUVN with LDA and SN-LDA is proposed to compensate the session and utterance variations and is shown to provide improvement in performance over the traditional approach of using LDA and/or SN-LDA followed by WCCN. An alternative approach is also introduced using probabilistic linear discriminant analysis (PLDA) approach to directly model the SUV. The combination of SUVN, LDA and SN-LDA followed by SUV PLDA modelling provides an improvement over the baseline PLDA approach. We also show that for this combination of techniques, the utterance variation information needs to be artificially added to full-length i-vectors for PLDA modelling.

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7 citations in Scopus
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7 citations in Web of Science®

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ID Code: 66930
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Speaker verification, i-vectors, PLDA, Utterance variation
DOI: 10.1016/j.specom.2014.01.004
ISSN: 1872-7182
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Past > Institutes > Information Security Institute
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Elsevier
Copyright Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Speech Communication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Speech Communication, Vol 59, DOI: 10.1016/j.specom.2014.01.004
Deposited On: 04 Feb 2014 23:58
Last Modified: 08 May 2016 04:44

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