TAILIEUCHUNG - Báo cáo khoa học: "Tracking Initiative in Collaborative Dialogue Interactions"

In this paper, we argue for the need to distinguish between task and dialogue initiatives, and present a model for tracking shifts in both types of initiatives in dialogue interactions. Our model predicts the initiative holders in the next dialogue turn based on the current initiative holders and the effect that observed cues have on changing them. Our evaluation across various corpora shows that the use of cues consistently improves the accuracy in the system' s prediction of task and dialogue initiative holders by 2-4 and 8-13 percentage points, respectively, thus illustrating the generality of our model. . | Tracking Initiative in Collaborative Dialogue Interactions Jennifer Chu-Carroll and Michael K. Brown Bell Laboratories Lucent Technologies 600 Mountain Avenue Murray Hill NJ 07974 . E-mail jencc mkb @ Abstract In this paper we argue for the need to distinguish between task and dialogue initiatives and present a model for ưacking shifts in both types of initiatives in dialogue interactions. Our model predicts the initiative holders in the next dialogue turn based on the current initiative holders and the effect that observed cues have on changing them. Our evaluation across various corpora shows that the use of cues consistently improves the accuracy in the system s prediction of task and dialogue initiative holders by 2-4 and 8-13 percentage points respectively thus illustrating the generality of our model. 1 Introduction Naturally-occurring collaborative dialogues are very rarely if ever one-sided. Instead initiative of the interaction shifts among participants in a primarily principled fashion signaled by features such as linguistic cues prosodic cues and in face-to-face interactions eye gaze and gestures. Thus for a dialogue system to interact with its user in a natural and coherent manner it must recognize the user s cues for initiative shifts and provide appropriate cues in its responses to user utterances. Previous work on mixed-initiative dialogues focused on tracking a single thread of control among participants. We argue that this view of initiative fails to distinguish between task initiative and dialogue initiative which together determine when and how an agent will address an issue. Although physical cues such as gestures and eye gaze play an important role in coordinating initiative shifts in face-to-face interactions a great deal of information regarding initiative shifts can be exffacted from utterances based on linguistic and domain knowledge alone. By taking into account such cues during dialogue interactions the system is better

• Báo cáo khoa học
• Tracking Initiative
• Collaborative Dialogue Interactions
• Jennifer Chu Carroll
• 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
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• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln