This paper presents an investigation into the use of adapted Gaussian mixture models in the context of open-set, text-independent 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.
Cite as: Fortuna, J., Sivakumaran, P., Ariyaeeinia, A., Malegaonkar, A. (2005) Open-set speaker identification using adapted Gaussian mixture models. Proc. Interspeech 2005, 1997-2000, doi: 10.21437/Interspeech.2005-627
@inproceedings{fortuna05_interspeech,
author={J. Fortuna and P. Sivakumaran and A. Ariyaeeinia and A. Malegaonkar},
title={{Open-set speaker identification using adapted Gaussian mixture models}},
year=2005,
booktitle={Proc. Interspeech 2005},
pages={1997--2000},
doi={10.21437/Interspeech.2005-627}
}