Understanding inexplicit utterances using vision for helper robots

Hanafiah, Z.M.; Yamazaki, C.; Nakamura, A.; Kuno, Yoshinori

doi:10.1109/icpr.2004.1333924

Cited by 10 publications

(4 citation statements)

References 5 publications

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“…Some robotic agents shift human attention in several ways including gaze turn, [28] head orientation, [29] reference term, [30] pointing gestures, [31] and body pose. [32] Most of these assumed that a human faces to the robot when their interaction begins.…”

Section: Related Workmentioning

confidence: 99%

Effect of robot’s gaze behaviors for attracting and controlling human attention

et al. 2013

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Controlling someone's attention can be defined as shifting his/her attention from the existing direction to another. To shift someone's attention, gaining attention and meeting gaze are two most important prerequisites. If a robot would like to communicate a particular person, it should turn its gaze to him/her for eye contact. However, it is not an easy task for the robot to make eye contact because such a turning action alone may not be effective in all situations, especially when the robot and the human are not facing each other or the human is intensely attending to his/her task. Therefore, the robot should perform some actions so that it can attract the target person and make him/her respond to the robot to meet gaze. In this paper, we present a robot that can attract a target person's attention by moving its head, make eye contact through showing gaze awareness by blinking its eyes, and directs his/her attention by repeating its eyes and head turns from the person to the target object. Experiments using 20 human participants confirm the effectiveness of the robot actions to control human attention.

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Section: Related Workmentioning

confidence: 99%

Effect of robot’s gaze behaviors for attracting and controlling human attention

et al. 2013

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“…various recognition technologies, such as speech recognition, pointing gesture recognition, and position detection of objects [18]- [19]. There are two approaches to improving the performance of these recognition technologies: the engineering approach and the entrainment approach.…”

Section: Introductionmentioning

confidence: 99%

Lexical entrainment in human-robot interaction: Can robots entrain human vocabulary?

Iio

Shiomi

Shinozawa

et al. 2009

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

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A communication robot must recognize a referred-to object to support us in daily life. However, using our wide human vocabulary, we often refer to objects in terms that are incomprehensible to the robot. This paper focuses on lexical entrainment to solve this problem. Lexical entrainment is the phenomenon of people tending to adopt the terms of their interlocutor. While this has been well studied in human-computer interaction, few published papers have approached it in human-robot interaction. To investigate how lexical entrainment occurs in human-robot interaction, we conduct experiments where people instruct the robot to move objects. Our results show that two types of lexical entrainment occur in human-robot interaction. We also discuss the effects of the state of objects on lexical entrainment. Finally, we developed a test bed system for recognizing a referred-to object on the basis of knowledge from our experiments.978-1-4244-3804-4/09/$25.00 ©2009 IEEE

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“…Some previous studies on joint attention used several social cues: for example, gaze [18][19], head and gaze [20], reference term and pointing [21][22]. Most of these assumed that the human faces to the robot when their interaction starts.…”

Section: Introductionmentioning

confidence: 99%

Controlling human attention through robot's gaze behaviors

Hoque

Onuki

Kobayashi

et al. 2011

2011 4th International Conference on Human System Interactions, HSI 2011

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Controlling someone's attention can be defined as shifting his/her attention from the existing direction to another. However, it is not easy task for a robot to shift a particular human's attention if they are not in face-to-face situation. If the robot would like to communicate a particular person, it should turn its gaze to that person and make eye contact to establish mutual gaze. However, only such a turning action is not enough to set up eye contact when the robot and the target person are not facing each other. Therefore, the robot should perform some actions so that it can attract the target person and meet their gaze. In this paper, we present a robot that can attract a target person's attention by moving its head, make eye contact through showing gaze awareness by blinking its eyes, and establish joint attention by repeating its head turns from the person and the target object. Experiments using twenty human participants confirm the effectiveness of the robot actions to control human attention.

show abstract

Understanding inexplicit utterances using vision for helper robots

Cited by 10 publications

References 5 publications

Effect of robot’s gaze behaviors for attracting and controlling human attention

Effect of robot’s gaze behaviors for attracting and controlling human attention

Lexical entrainment in human-robot interaction: Can robots entrain human vocabulary?

Controlling human attention through robot's gaze behaviors

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