If a dialog system can respond to a user as naturally as a human, the interaction will be smoother. In this research, we aim to develop a dialog system by emulating the human behavior in a chat-like dialog. In this paper, we developed a dialog system which could generate chat-like responses and their timing using a decision tree. The system could perform “collaborative completion,” “
” (back-channel) and so on. The decision tree utilized the pitch and the power contours of user’s utterance, recognition hypotheses, and response preparation status of the response generator, at every time segment as features to generate response timing.
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten