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...
We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
Homograph ambiguity is an original issue in Text-to-Speech (TTS). To disambiguate homograph, several efficient approaches have been proposed such as part-of-speech (POS) n-gram, B...
Manymethods for analyzing biological problems are constrained by problemsize. Theability to distinguish betweenrelevant andirrelevant features of a problemmay allowa problemto be ...
In text management tasks, the dimensionality reduction becomes necessary to computation and interpretability of the results generated by machine learning algorithms. This paper de...