Traditionally listener response prediction models are learned from pre-recorded dyadic interactions. Because of individual differences in behavior, these recordings do not capture...
Iwan de Kok, Derya Ozkan, Dirk Heylen, Louis-Phili...
To reduce the complexity of studying a parallel mechanism for natural language learning and understanding which supports both utterance and discourse processing, we propose a comp...
Theme network is a semantic network of document specific themes. So far Natural Language Processing (NLP) research patronized much of topic based summarizer system, unable to captu...
In this paper, we address the tasks of recognition and interpretation of affect communicated through text messaging. The evolving nature of language in online conversations is a ma...
Alena Neviarouskaya, Helmut Prendinger, Mitsuru Is...
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...