V. Hung, A. Gonzalez, and R. F. DeMara
Department of Electrical Engineering and Computer Science,
University of Central Florida,
Orlando, FL,
USA

victor@isl.ucf.edu, gonzalez@ucf.edu, demara@mail.ucf.edu


V. Hung, A. Gonzalez, R. F. DeMara, "Dialog Management For Rapid-Prototyping of Speech-Based Training Agents", Interservice/Industry Training, Simulation & Education Conference, Orlando, Florida, USA, Nov 29-Dec 2, 2010.

Speech-based training agents can be described as virtual humans posing as interactive training characters with the
capability to communicate in a spoken conversational manner. While creating this technology, developers face two
stumbling blocks: 1) modeling the agent and its training knowledge is a time-consuming and tedious task, and 2)
modern speech recognition software suffers from high Word-Error Rates caused by noisy environmental conditions.
This paper presents a dialog management architecture that addresses these problems using the Context-Based
Reasoning paradigm. The system minimizes the time necessary to build the training knowledge in the instructional
agent, as well as tolerates the relatively high Word-Error Rates related to automatic speech recognition. Ultimately,
these advantages lead to quick development of speech-based training agents. The dialog manager was directly
implemented into the LifeLike Avatar, an embodied conversational agent funded by the National Science
Foundation. A set of quantitative results is presented to reflect the effectiveness of the system.