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
Aim

  • To build Social Robot/Agent

  • Sub goal

  • To establish

    • Evaluation methods

    • Design guidelines

      for communication of human-robot/agent


Method l.jpg
Method

  • To measure the influence of Agent/Robot on users

  • Acceptance ratio of agent/robot recommendation


Color name selection task l.jpg
Color name selection task

• No “correct” answer

• Easy to be influenced

Blue or Green?

Cobalt green or emerald green?

Skin color or KARE-IRO?

SUMIRE-IRO or AYAME-IRO?

----

----

Total:30 questions.

(from color name text book)


Four experiments l.jpg
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

http://www.ntt.co.jp/tr/

Back number -> Sep. 2003


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

Agent

Robot

Agent

Robot

• Conditions: 30 questions, 30 subjects in each group

‐Same question sequences, same voice, similar gesture

• Measurement: acceptance ratio, questionnaire



Experiment 1 result l.jpg
Experiment 1: Result

• Acceptance:agent > robot (p<.01)

• Familiarity:independent


Slide9 l.jpg

Gap

Gap

Gap

Initial expectation

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

same as subjects.

agent

robot

×


Experiment 2 compare in physical world l.jpg
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)



Experiment 2 result l.jpg
Experiment 2: Result

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

robot>> no recommendation ( p < 0.01)


Slide13 l.jpg

×

×

Embodiment and communication

Experiment 1 and 2: Results

Consistency matters.

Physical world

Media world

agent

robot


Why robot is better l.jpg
Why robot is better?

  • Easy to detect gaze

    • Eye contact

    • Shared attention/joint attention

Measure the effect of

eye contact and shared-attention


Experiment 3 effect of eye contact mutual gaze l.jpg
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



Selection ratio l.jpg
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)


Experiment 4 effect of shared attention l.jpg
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?


Establishing shared attention l.jpg
Establishing shared-attention

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

  • Eye contact established by face tracking

Example: video


Experimental conditions l.jpg
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).


Sa time and selection ratio l.jpg
SA time and selection ratio

  • No correlation

Selection

ratio

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


Clustering subjects by teg ego gram l.jpg
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


High low teg measurement and sa time l.jpg
High/Low TEG measurement and SA time.

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


Sa time and selection ratio high ac low cp group l.jpg
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.