In this paper, we propose a novel speaker adaptation technique, regularized-MLLR, for Computer Assisted Language Learning (CALL) systems. This method uses a linear combination of ...
Dean Luo, Yu Qiao, Nobuaki Minematsu, Yutaka Yamau...
The vast majority of medical computer-based training (CBT) systems aim at problem-oriented case based training. A crucial issue in the design of CBT systems is the selection of ap...
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
Theoretical models for the evaluation of quickly improving search strategies, like limited discrepancy search, are based on specific assumptions regarding the probability that a va...
Appropriate feature selection is a very crucial issue in any machine learning framework, specially in Maximum Entropy (ME). In this paper, the selection of appropriate features for...