A probabilistic measure of modality reliability in speaker verification
Jonas Richiardi, Plamen J. Prodanov, Andrzej Drygajlo · 2005
In this paper, a probabilistic measure for reliability of speaker verification under noisy acoustic conditions is proposed. A Ba-yesian network is used to estimate a probability for verification errors, given the GMM-based speaker verification system output and additional information about the level of acoustic noise. In particular, the log-likelihood ratio and a signal-to-noise related fea-ture are used to account for the adverse acoustic conditions. The probabilistic measure is subsequently employed in governing a re-pair sequence of trials for acquiring additional speech presenta-tions which are less likely to lead to unreliable verification. The potential of the proposed method is tested through cross-validation experiments. Finally, the benefits of the repair sequence in terms of verification accuracy is evaluated on a noisy environment speaker verification task. 1.