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 authors propose a co-adaptive approach to controlling parameters for coevolution-based learning classifier systems. By taking advantage of the on-line incremental learning capa...
There is a genuine demand for personalization and guidance in learning systems, as well as in general commercial learning systems for the WWW, and further, for the new, emerging S...
Alexandra I. Cristea, Angelo Wentzler, Egbert Heuv...
This paper is a comprehensive presentation of our efforts to support mobile learning. We are developing the Intelligent Mobile Learning System which provides adaptive course and a...
We present an automatic on-line adaptation mechanism to the writer’s handwriting style for the recognition of isolated handwritten characters. The classifier is based on a Fuzz...