4th International Conference on Spoken Language Processing
Philadelphia, PA, USA
In order to improve the performances of speaker recognition on telephone speech, we investigate the ability to cooperate of two different natures modelizations: the GMM and the ARVM. For the cooperation and competition of the GMM and ARVM modelizations, we used normalized measures. We develop two approaches for these cooperation and competition: a global approach and an analytical approach. We investigate experiments on whole sentences or selected phonetic segments. Theses approaches allow us to obtain performances improvements for both cooperation and competition, and good results on 168 speakers of the NTIMIT database (GMM: 61.7 %, ARVM: 78.1 %, cooperation: 79.9 % and competition: 82.6 %).
Bibliographic reference. Floch, J.-L. Le / Montacié, C. / Caraty, M.-J. (1996): "GMM and ARVM cooperation and competition for text-independent speaker recognition on telephone speech", In ICSLP-1996, 2411-2414.