Given that, should i respond?: contextual addressee estimation in multi-party human-robot interactions

Authors:
Dinesh Babu Jayagopi;Jean-Marc Odobez
Affiliations:
Idiap Research Institute, Martigny, Switzerland;Idiap Research Institute and PFL, Martigny, Switzerland
Venue:
Proceedings of the 8th ACM/IEEE international conference on Human-robot interaction
Year:
2013

Citing 3
Cited 1

Identifying the addressee in human-human-robot interactions based on head pose and speech

Proceedings of the 6th international conference on Multimodal interfaces
Identifying the intended addressee in mixed human-human and human-computer interaction from non-verbal features

ICMI '05 Proceedings of the 7th international conference on Multimodal interfaces
Making virtual conversational agent aware of the addressee of users' utterances in multi-user conversation using nonverbal information

ICMI '11 Proceedings of the 13th international conference on multimodal interfaces

Context aware addressee estimation for human robot interaction

Proceedings of the 6th workshop on Eye gaze in intelligent human machine interaction: gaze in multimodal interaction

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we investigate the task of addressee estimation in multi-party interactions. For every utterance from a human participant, the robot should know if it was being addressed or not, so as to respond and behave accordingly. To accomplish this various cues could be made use of: the most important being gaze cues of the speaker. Apart from this several other cues can act as contextual variables to improve the estimation accuracy of this task. For example, the gaze cue of other participants, and the long-term or short-term dialog context. In this paper we investigate the possibility to combine such information from diverse sources to improve the addressee estimation task. For this study, we use 11 interactions with a humanoid robot NAO1 giving quiz to two human participants.