TAILIEUCHUNG - Báo cáo khoa học: "Targeted Help for Spoken Dialogue Systems: intelligent feedback improves naive users' performance"

We present experimental evidence that providing naive users of a spoken dialogue system with immediate help messages related to their out-of-coverage utterances improves their success in using the system. A grammar-based recognizer and a Statistical Language Model (SLM) recognizer are run simultaneously. If the grammar-based recognizer suceeds, the less accurate SLM recognizer hypothesis is not used. When the grammar-based recognizer fails and the SLM recognizer produces a recognition hypothesis, this result is used by the Targeted Help agent to give the user feedback on what was recognized, a diagnosis of what was problematic about the utterance, and a related. | Targeted Help for Spoken Dialogue Systems intelligent feedback improves naive users performance Beth Ann Hockey Research Institute for Advanced Computer Science RIACS NASA Ames Research Center Moffet Field CA 94035 bahockey@ Oliver Lemon School of Informatics University of Edinburgh 2 Buccleugh Place Edinburgh EH8 9LW UK olemon Ellen Campana Department of Brain and Cognitive Sciences University of Rochester Rochester NY 14627 ecampana@ Laura Hiatt Center for the Study of Language and Information CSLI Stanford University 210 Panama St Stanford CA 94305 lahiatt@ Gregory Aist RIACS NASA Ames Research Center Moffet Field CA 94035 aist@ James Hieronymus RIACS NASA Ames Research Center Moffet Field CA 94035 Alexander Gruenstein BeVocal Inc. 685 Clyde Avenue Mountain View CA 94043 John Dowding RIACS NASA Ames Research Center Moffet Field CA 94035 jimh@ agruenstein@ jdowding@ Abstract We present experimental evidence that providing naive users of a spoken dialogue system with immediate help messages related to their out-of-coverage utterances improves their success in using the system. A grammar-based recognizer and a Statistical Language Model SLM recognizer are run simultaneously. If the grammar-based recognizer suceeds the less accurate SLM recognizer hypothesis is not used. When the grammar-based recognizer fails and the SLM recognizer produces a recognition hypothesis this result is used by the Targeted Help agent to give the user feedback on what was recognized a diagnosis of what was problematic about the utterance and a related in-coverage example. The in-coverage example is intended to encourage alignment between user inputs and the language model of the system. We report on controlled ex periments on a spoken dialogue system for command and control of a simulated robotic helicopter. 1 Introduction Targeted Help makes use of user utterances that are out-of-coverage of the main

• Báo cáo khoa học
• Targeted Help
• Spoken Dialogue Systems
• intelligent feedback improves naive users performance
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• Long Papers
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln