User Modeling by Using Bag-of-Behaviors for Building a Dialog System Sensitive to the Interlocutor's Internal State
Yuya Chiba, Masashi Ito, Takashi Nose, Akinori Ito · 2014
When using spoken dialog systems in ac-tual environments, users sometimes aban-don the dialog without making any in-put utterance. To help these users before they give up, the system should know why they could not make an utterance. Thus, we have examined a method to estimate the state of a dialog user by capturing the user’s non-verbal behavior even when the user’s utterance is not observed. The pro-posed method is based on vector quan-tization of multi-modal features such as non-verbal speech, feature points of the face, and gaze. The histogram of the VQ code is used as a feature for determining the state. We call this feature “the Bag-of-Behaviors. ” According to the experi-mental results, we prove that the proposed method surpassed the results of conven-tional approaches and discriminated the target user’s states with an accuracy of more than 70%. 1