Dialogue Patterns and Misunderstandings

Abstract

Disruptive errors are common in many human-computer (HC) dialogues. We manually applied initiative and dialogue act annotations to HC dialogues in the travel domain in an effort to find patterns that are predictive of misunderstandings. While we found some interesting patterns of dialogue acts, we also found that a detailed understanding of the misunderstandings in our data required us to perform more in-depth analysis than is possible just by examining dialogue acts. Our hope is that analyses such as these will inform the design of HC dialogue systems, so that systems may predict problematic situations in order to deal with them more effectively.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
AD1133164

Entities

People

  • John Aberdeen
  • Lisa Ferro

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Automated Speech Recognition
  • Computational Linguistics
  • Computational Science
  • Computer Languages
  • Computers
  • Data Sets
  • Dialogue Systems
  • Human-Machine Interaction
  • Indicators
  • Language
  • Linguistics
  • Machine Learning
  • Natural Language Processing
  • New York
  • Recognition
  • Recovery

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Military Engineering.
  • Systems Analysis and Design