We use machine learners trained on a combination of acoustic confidence and pragmatic plausibility features computed from dialogue context to predict the accuracy of incoming n-be...
We examine the utility of speech and lexical features for predicting student emotions in computerhuman spoken tutoring dialogues. We first annotate student turns for negative, neu...
As spoken dialogue systems become deployed in increasingly complex domains, they face rising demands on the naturalness of interaction. We focus on system responsiveness, aiming t...
This article presents a multi-agent dialogue system. We show how a collection of relatively simple agents is able to treat complex dialogue phenomena and deal successfully with di...
Hugo Pinto, Yorick Wilks, Roberta Catizone, Alexie...
We propose an efficient dialogue management for an information navigation system based on a document knowledge base with a spoken dialogue interface. In order to perform robustly ...