Conference Paper Probabilistic Prediction in Multiclass Classification Derived for Flexible Text-Prompted Speaker Verification

Kurogi, Shuichi  ,  Sakashita, Shota  ,  Takeguchi, Satoshi  ,  Ueki, Takuya  ,  Matsuo, Kazuya

9489 ( 1 )  , pp.216 - 225 , 2015-11-09 , Springer
So far, we have presented amethod for text-promptedmultistep speaker verification using GEBI (Gibbs-distribution based extended Bayesian inference) for reducing single-step verification error, where we use thresholds for acceptance and rejection but the tuning is not so easy and affects the performance of verification. To solve the problem of thresholds, this paper presents a method of probabilistic prediction in multiclass classification for solving verification problem.We also present loss functions for evaluating the performance of probabilistic prediction. By means of numerical experiments using recorded real speech data, we examine the properties of the present method using GEBI and BI (Bayesian inverence) and show the effectiveness and the risk of probability loss in the present method.
22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015

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