Open-set speaker identification using adapted Gaussian mixture models

J. Fortuna, P. Sivakumaran, A. Ariyaeeinia, A. Malegaonkar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)


This paper presents an investigation into the use of adapted Gaussian mixture models in the context of open-set, text-inde-pendent speaker identification (OSTI-SI). The study includes a scheme for using the fast-scoring method which has been proposed for speaker verification. Furthermore, it provides an evaluation of various score normalisation methods in the proposed OSTI-SI framework. The dataset used for the experimental investigation is based on NIST SRE2003 1-speaker detection task. It is shown that significant improvements can be achieved if only a single mixture is used in the fast-scoring technique. Furthermore, it is experimentally observed that comparable performance is obtained using unconstrained cohort normalisation, T-norm and TZ-norm. The paper provides a detailed description of the experimental set up, and presents an analysis of the results obtained.

Original languageEnglish
Title of host publicationProc. 9th European Conference on Speech Communication and Technology
Number of pages4
Publication statusPublished - 2005
Event9th European Conference on Speech Communication and Technology - Lisbon, Portugal
Duration: 4 Sept 20058 Sept 2005


Conference9th European Conference on Speech Communication and Technology

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