Abstract
This paper shows a description of the system used in the ISCSLP06 Speaker Recognition Evaluation, text independent cross-channel speaker verification task. It is a discriminative Artificial Neural Network-based system, using the Non-Target Incremental Learning method to select world representatives. Two different training strategies have been followed: (i) to use world representative samples with the same channel type as the true model, (ii) to select the world representatives from a pool of samples without channel type identification. The best results have been achieved with the first alternative, but with the appearance of the additional problem of the true model channel type recognition. The system used in this task will also be shown.
This work has been supported by the Ministerio de Ciencia y Tecnología, Spain, under Project TIC2003-08382-C05-03.
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Vivaracho, C.E. (2006). ISCSLP SR Evaluation, UVA–CS_es System Description. A System Based on ANNs. In: Huo, Q., Ma, B., Chng, ES., Li, H. (eds) Chinese Spoken Language Processing. ISCSLP 2006. Lecture Notes in Computer Science(), vol 4274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11939993_55
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DOI: https://doi.org/10.1007/11939993_55
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