State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
In this paper we consider the problem of building a system to predict readability of natural-language documents. Our system is trained using diverse features based on syntax and l...
Rohit J. Kate, Xiaoqiang Luo, Siddharth Patwardhan...
Abstract—We present an extension of automatic image annotation that takes the context of a picture into account. Our core assumption is that users do not only provide individual ...
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...
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation...