Error handling in the RavenClaw dialog management framework

We describe the error handling architectture underlying the RavenClaw dialog management framework. The architecture provides a robust basis for current and future research in error detection and recovery. Several objectives were pursued in its development: task-independence, ease-of-use, adaptability and scalability. We describe the key aspects of architectural design which confer these properties, and discuss the deployment of this architectture in a number of spoken dialog systems spanning several domains and interaction types. Finally, we outline current research projects supported by this architecture.

[1]  Marilyn A. Walker,et al.  Using Natural Language Processing and discourse Features to Identify Understanding Errors , 2000, ICML.

[2]  Takaaki Hori,et al.  Spoken Interactive ODQA System: SPIQA , 2003, ACL.

[3]  Alexander I. Rudnicky,et al.  Ravenclaw: dialog management using hierarchical task decomposition and an expectation agenda , 2003, INTERSPEECH.

[4]  T.K. Harris,et al.  A research platform for multi-agent dialogue dynamics , 2004, RO-MAN 2004. 13th IEEE International Workshop on Robot and Human Interactive Communication (IEEE Catalog No.04TH8759).

[5]  Emiel Krahmer,et al.  Error spotting in human-machine interaction , 1999 .

[6]  S. Singh,et al.  Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System , 2011, J. Artif. Intell. Res..

[7]  David Traum.  On Clark and Schaefer’s Contribution Model and its applicability to Human-Computer Collaboration , 2007 .

[8]  A.I. Rudnicky,et al.  Constructing accurate beliefs in spoken dialog systems , 2005, IEEE Workshop on Automatic Speech Recognition and Understanding, 2005..

[9]  Alexander I. Rudnicky,et al.  Sorry and I Didn’t Catch That! - An Investigation of Non-understanding Errors and Recovery Strategies , 2005, SIGDIAL.

[10]  Steve Young,et al.  Automatic learning of dialogue strategy using dialogue simulation and reinforcement learning , 2002 .

[11]  Maxine Eskénazi,et al.  Let's go public! taking a spoken dialog system to the real world , 2005, INTERSPEECH.

[12]  Marilyn A. Walker,et al.  Quantitative and Qualitative Evaluation of Darpa Communicator Spoken Dialogue Systems , 2001, ACL.

[13]  Herbert H. Clark,et al.  Contributing to Discourse , 1989, Cogn. Sci..

[14]  Diane J. Litman,et al.  ITSPOKE: An Intelligent Tutoring Spoken Dialogue System , 2004, NAACL.

[15]  Tatsuya Kawahara,et al.  Flexible Mixed-Initiative Dialogue Management using Concept-Level Confidence Measures of Speech Recognizer Output , 2000, COLING.

[16]  Gregory A. Sanders,et al.  Effects of word error rate in the DARPA communicator data during 2000 and 2001 , 2002, INTERSPEECH.

[17]  Jeremy H. Wright,et al.  Using Natural Language Processing and Discourse Features to Identify Understanding Errors in a Spoken Dialogue System , 2000 .

[18]  Janet E. Cahn,et al.  A Psychological Model of Grounding and Repair in Dialog , 1999 .

[19]  Eric Horvitz,et al.  Conversation as Action Under Uncertainty , 2000, UAI.