Title

Context-Centric Speech-Based Human-Computer Interaction

Authors

Authors

V. C. Hung;A. J. Gonzalez

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Int. J. Intell. Syst.

Keywords

LANGUAGE; BEHAVIOR; DIALOGUE; Computer Science, Artificial Intelligence

Abstract

This paper describes research that addresses the problem of dialog management from a strong, context-centric approach. We further present a quantitative method of measuring the importance of contextual cues when dealing with speech-based human-computer interactions. It is generally accepted that using context in conjunction with a human input, such as spoken speech, enhances a machine's understanding of the user's intent as a means to pinpoint an adequate reaction. For this work, however, we present a context-centric approach in which the use of context is the primary basis for understanding and not merely an auxiliary process. We employ an embodied conversation agent that facilitates the seamless engagement of a speech-based information-deployment entity by its human end user. This dialog manager emphasizes the use of context to drive its mixed-initiative discourse model. Atypical, modern automatic speech recognizer (ASR) was incorporated to handle the speech-to-text translations. As is the nature of these ASR systems, the recognition rate is consistently less than perfect, thus emphasizing the need for contextual assistance. The dialog system was encapsulated into a speech-based embodied conversation agent platform for prototyping and testing purposes. Experiments were performed to evaluate the robustness of its performance, namely through measures of naturalness and usefulness, with respect to the emphasized use of context. The contribution of this work is to provide empirical evidence of the importance of conversational context in speech-based human-computer interaction using a field-tested context-centric dialog manager. (C) 2013 Wiley Periodicals, Inc.

Journal Title

International Journal of Intelligent Systems

Volume

28

Issue/Number

10

Publication Date

1-1-2013

Document Type

Article

Language

English

First Page

1010

Last Page

1037

WOS Identifier

WOS:000322579900005

ISSN

0884-8173

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