Effect of shared attention for human robot interaction
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Effect of Shared-attention for Human-Robot Interaction Junji Yamato [email protected] NTT Communication Science Labs., NTT Corp. Japan Kazuhiko Shinozawa, Futoshi Naya ATR Intelligent Robot and Communication Labs. Aim To build Social Robot/Agent Sub goal To establish Evaluation methods

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Effect of shared attention for human robot interaction l.jpg
Effect of Shared-attention for Human-Robot Interaction

Junji Yamato

[email protected]

NTT Communication Science Labs., NTT Corp. Japan

Kazuhiko Shinozawa, Futoshi Naya

ATR Intelligent Robot and Communication Labs.

Slide2 l.jpg

  • To build Social Robot/Agent

  • Sub goal

  • To establish

    • Evaluation methods

    • Design guidelines

      for communication of human-robot/agent

Method l.jpg

  • To measure the influence of Agent/Robot on users

  • Acceptance ratio of agent/robot recommendation

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Color name selection task

• No “correct” answer

• Easy to be influenced

Blue or Green?

Cobalt green or emerald green?

Skin color or KARE-IRO?




Total:30 questions.

(from color name text book)

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Four experiments

  • Compared agent and robot

  • Compared agent and robot in physical world

  • Measured the effect of eye contact

  • Measured the effect of shared-attention

Detailed description of Experiment 1 and 2

Shinozawa, K., Naya, F., Yamato, J., and Kogure, K. Differences in Effect of Robot and Screen Agent Recommendations on Human Decision-Making , IJHCS (to appear)

Experiment 1, 2, and description of K4(robot)

Yamato, J., Shinozawa, K., Brooks, R., and Naya, F. Human-Robot Dynamic Social Interaction. NTT Technical Review 1, 6(2003), 37-43.

Available on-line


Back number -> Sep. 2003

Experiment 1 compare agent and robot l.jpg
Experiment 1:Compare Agent and Robot





• Conditions: 30 questions, 30 subjects in each group

‐Same question sequences, same voice, similar gesture

• Measurement: acceptance ratio, questionnaire

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Experiment 1: Result

• Acceptance:agent > robot (p<.01)

• Familiarity:independent

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Initial expectation

Robot has more influence because it lives in 3D world,

same as subjects.




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Experiment 2: Compare in physical world

Color plate

Button box

Button box

  • No recommendation (30 subjects)

  • Recommendation by robot(31 subjects)

  • Recommendation by agent (30 subjects)

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Experiment 2: Result

• selection ratio:robot > agent( p < 0.05)

robot>> no recommendation ( p < 0.01)

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Embodiment and communication

Experiment 1 and 2: Results

Consistency matters.

Physical world

Media world



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Why robot is better?

  • Easy to detect gaze

    • Eye contact

    • Shared attention/joint attention

Measure the effect of

eye contact and shared-attention

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Experiment 3: Effect of eye contact (mutual gaze)

  • Eye contact was established by face tracking

  • Eye contact time: period that subject looked at robot and robot looked at subject

  • Eye contact time and selection ratio?

  • Two groups (14 subjects each)

    • Eye contact, and NO eye contact

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Selection ratio

  • Higher selection ratio for eye contact group

  • K4: No E.C. < E.C.(p=0.012)

  • Rabbit: No E.C. < E.C. (p=0.003)

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Experiment 4: Effect of shared-attention

  • Shared attention:

    • Period that robot looks at an object and subject looks at the same object. (color plate, button box)

  • SA time and selection ratio

    • Is there correlation?

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Establishing shared-attention

  • Robot looks at color plate and button box by prepared program

  • Eye contact established by face tracking

Example: video

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Experimental conditions

  • 28 subjects

  • SA time = 51.7 sec (total for 30 questions)

    • (Longer than in Experiment 3 )

  • Selection ratio. Average: 0.57 S.D.= 0.14

  • Some subjects were positive, and others were not. Clear contrast, from the questionnaire.

    Example: Robot is prompting wrong choice. I feel the robot forced me to select his recommendation (negative).

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SA time and selection ratio

  • No correlation



Shared-Attention time (count) 50count=1sec.

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Clustering subjects by TEG(Ego-gram)

  • Ego-gram based on transactional analysis

  • Measure three ego-states by questionnaire

    • CP, NP (critical parent, nurturing parent)

    • A (adult)

    • FC, AC (free child, adapted child)

  • TEG (Tokyo Univ. Egogram)is common in Japan

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High/Low TEG measurement and SA time.

  • Strong correlation in SA time and acceptance ratio for high AC (Adapted Child) group

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SA time and selection ratio (high AC & low CP group)

  • Positive correlation(Speaman’s r=0.51,p=0.051).

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SA time and selection ratio

  • High-SA group = high selection ratio (p<0.05)

(high AC group)

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Result and Discussion

  • High AC subject (obedient type) showed positive correlation between SA time and selection ratio.

  • No significant difference between SA time itself and selection ratios for high AC and low AC groups

  • Eye contact and shared-attention promote close communication. Some people like such intimate relation, but others don’t. It depends on the character.

  • SA is effective. Even SA was not “actually” realized. We do not need to develop image understanding technology; we just have to fake it.