Integrating Miscommunication Analysis in Natural Language Interface Design for a Service Robot

Natural language user interfaces for robots with cognitive capabilities should be designed to reduce the occurrence of miscommunication in order to be perceived as providing a smooth and intuitive interaction to its users. This paper describes how miscommunication analysis is integrated in the design process. Observations from 12 user sessions revealed that users misunderstand the robot's functionality; and that feedback sometimes is ill-timed with respect to the situation. We provide a set of design implications to prevent errors from occurring, to influence or adapt to users' behavior

[1]  Elizabeth Zoltan-Ford,et al.  How to Get People to Say and Type What Computers Can Understand , 1991, Int. J. Man Mach. Stud..

[2]  A. Green,et al.  Task-oriented dialogue for CERO: a user-centered approach , 2001, Proceedings 10th IEEE International Workshop on Robot and Human Interactive Communication. ROMAN 2001 (Cat. No.01TH8591).

[3]  R. Sun Cognition and Multi-Agent Interactions: From Cognitive Modeling to Social Simulation , 2005 .

[4]  P. Dillenbourg,et al.  Miscommunication in Multi-modal Collaboration , 1995 .

[5]  Anders Green,et al.  Developing a ContextualizedMultimodal Corpus for Human-Robot Interaction , 2006, LREC.

[6]  David Traum,et al.  The Error Is the Clue: Breakdown In Human-Machine Interaction , 2006 .

[7]  M. Pickering,et al.  Toward a mechanistic psychology of dialogue , 2004, Behavioral and Brain Sciences.

[8]  Steven L. Alter Which Life Cycle - Work System, Information System, or Software? , 2001, Commun. Assoc. Inf. Syst..

[9]  Alexander I. Rudnicky,et al.  Error handling in the RavenClaw dialog management framework , 2005, EMNLP 2005.

[10]  Yoris A. Au Design Science I: The Role of Design Science in Electronic Commerce Research , 2001, Commun. Assoc. Inf. Syst..

[11]  Andrea Lockerd Thomaz,et al.  Effects of nonverbal communication on efficiency and robustness in human-robot teamwork , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Arne Jönsson,et al.  Wizard of Oz studies: why and how , 1993, IUI '93.

[13]  Marilyn A. Walker,et al.  PARADISE: A Framework for Evaluating Spoken Dialogue Agents , 1997, ACL.

[14]  Nicole Yankelovich,et al.  How do users know what to say? , 1996, INTR.

[15]  Gernot A. Fink,et al.  A multi-modal dialog system for a mobile robot , 2004, INTERSPEECH.

[16]  Chris Baber,et al.  Designing habitable dialogues for speech-based interaction with computers , 2001, Int. J. Hum. Comput. Stud..

[17]  J. Gregory Trafton,et al.  Cognition and Multi-Agent Interaction: Communicating and Collaborating with Robotic Agents , 2005 .

[18]  Susan Brennan,et al.  Interaction and feedback in a spoken language system: a theoretical framework , 1995, Knowl. Based Syst..

[19]  Lynette Hirschman,et al.  Finding Errors Automatically in Semantically Tagged Dialogues , 2001, HLT.

[20]  Michael Kipp,et al.  Gesture generation by imitation: from human behavior to computer character animation , 2005 .

[21]  M. Rey,et al.  The Error Is the Clue: Breakdown In Human-Machine Interaction , 2003 .

[22]  Colin Potts,et al.  Design of Everyday Things , 1988 .