The "Etiquette Quotient"; Evaluating Social Skills in Conversational Avatars

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-04-C-R221
Agency Tracking Number: 04SB1-0155
Amount: $98,698.00
Phase: Phase I
Program: SBIR
Awards Year: 2004
Solicitation Year: 2004
Solicitation Topic Code: SB041-009
Solicitation Number: 2004.1
Small Business Information
1272 Raymond Ave, St. Paul, MN, 55108
DUNS: 103477993
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Christopher Miller
 Chief Scientist
 (612) 716-4015
Business Contact
 Harry Funk
Title: Vice President, R&D
Phone: (612) 578-7438
Research Institution
Making avatars react appropriately in social interaction--to take offense when reasonable, to give deference where appropriate, etc.-- is a more fundamental need for believability and cost-effectiveness than is accuracy in appearance, especially for military applications such as cross-cultural training. We propose using a rich, universal theory of human-human "politeness" behaviors and the culture-specific interpretive frameworks for them (labeled "etiquette") from sociology, linguistics and anthropology to create a computational model of social behavior expectations. This model will link observable and inferred aspects of power and familiarity relationships, the degree of imposition of an act (all of which have implications for roles and intents) and the actor's character to produce politeness behaviors expectations. By using observations of politeness behaviors (or its lack), the same model permits inferences and updates about those attributes. In Phase I, we will refine and implement this model to provide a computational believability metric based on the delta between observed and expected politeness behaviors--an "Etiquette Quotient" (EQ)--of an actor in context. We will also validate and tune this measure in an experiment using avatars. In Phase II, we will expand this model with cross-cultural etiquette libraries and use it dynamically adapt avatars' social behavior.

* Information listed above is at the time of submission. *

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