Simon Plays Simon Says: The Timing of Turn-Taking in an imitation Game

Abstract

Turn-taking is fundamental to the way humans engage in information exchange, but robots currently lack the turn-taking skills required for natural communication. In order to bring effective turn-taking to robots, we must first understand the underlying processes in the context of what is possible to implement. We describe a data collection experiment with an interaction format inspired by "Simon says," a turn-taking imitation game that engages the channels of gaze, speech, and motion. We analyze data from 23 human subjects interacting with a humanoid social robot and propose the principle of minimum necessary information (MNI) as a factor in determining the timing of the human response. We also describe the other observed phenomena of channel exclusion efficiency, and adaptation. We discuss the implications of these principles and propose some ways to incorporate our findings into a computational model of turn-taking.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2012
Accession Number
ADA556627

Entities

People

  • Andrea L. Thomaz
  • Crystal Chao
  • Jinhan Lee
  • Momotaz Begum

Organizations

  • Georgia Tech

Tags

DTIC Thesaurus Topics

  • Computer Programming
  • Control Systems
  • Data Sets
  • Detectors
  • Efficiency
  • Human Behavior
  • Human-Robot Interaction
  • Information Exchange
  • Language
  • Linguistics
  • Models
  • Negotiations
  • Observation
  • Probabilistic Models
  • Probability
  • Psychology
  • Robots

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • Autonomy
  • Autonomy - Human-Robot Interaction