Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper we attempt to train and combine the base classifiers using an adaptive policy. This policy is ...
This paper investigates the recognition of group actions in meetings. A statistical framework is proposed in which group actions result from the interactions of the individual participants. The group actions are modelled using different HMM-based approache ...
The purpose of this paper is to unify several of the state-of-the-art score normalization techniques applied to text-independent speaker verification systems. We propose a new framework for this purpose. The two well-known Z- and T-normalization techniques ...
IEEE Institute of Electrical and Electronics Engineers2005
