TY - JOUR
T1 - Developing preferential attention to a speaker
T2 - A robot learning to recognise its carer
AU - Murray, J.C.
AU - Cañamero, Lola
N1 - “This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/ALIFE.2009.4937697
PY - 2009
Y1 - 2009
N2 - In this paper we present a socially interactive multi-modal robotic head, ERWIN - Emotional Robot With Intelligent Networks, capable of emotion expression and interaction via speech and vision. The model presented shows how a robot can learn to attend to the voice of a specific speaker, providing a relevant emotional expressive response based on previous interactions. We show three aspects of the system; first, the learning phase, allowing the robot to learn faces and voices from interaction. Second, recognition of the learnt faces and voices, and third, the emotion expression aspect of the system. We show this from the perspective of an adult and child interacting and playing a small game, much like an infant and caregiver situation. We also discuss the importance of speaker recognition in terms of human-robot-interaction and emotion, showing how the interaction process between a participant and ERWIN can allow the robot to prefer to attend to that person.
AB - In this paper we present a socially interactive multi-modal robotic head, ERWIN - Emotional Robot With Intelligent Networks, capable of emotion expression and interaction via speech and vision. The model presented shows how a robot can learn to attend to the voice of a specific speaker, providing a relevant emotional expressive response based on previous interactions. We show three aspects of the system; first, the learning phase, allowing the robot to learn faces and voices from interaction. Second, recognition of the learnt faces and voices, and third, the emotion expression aspect of the system. We show this from the perspective of an adult and child interacting and playing a small game, much like an infant and caregiver situation. We also discuss the importance of speaker recognition in terms of human-robot-interaction and emotion, showing how the interaction process between a participant and ERWIN can allow the robot to prefer to attend to that person.
U2 - 10.1109/ALIFE.2009.4937697
DO - 10.1109/ALIFE.2009.4937697
M3 - Article
VL - 2009
SP - 77
EP - 84
JO - Procs IEEE Symposium on Artificial Life,
JF - Procs IEEE Symposium on Artificial Life,
ER -