Context-Centric Speech-Based Human-Computer Interaction

    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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