Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
The goal of my research is to understand speech input in a continuous manner by treating the input stream as fragmental utterances. This allows us to use various approaches to pre...
This paper presents a new approach to language model construction, learning a language model not from text, but directly from continuous speech. A phoneme lattice is created using...
Graham Neubig, Masato Mimura, Shinsuke Mori, Tatsu...
In this demonstration paper we present a stream query processor capable of handling media (audio, video, motion ...) and feature streams. We show that due to their inherent semant...
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...