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AAAI 2004

SCoT: A Spoken Conversational Tutor

System Paper Intelligent Systems Demonstrations Artificial Intelligence

Abstract

We describe SCoT, a Spoken Conversational Tutor, which has been implemented in order to investigate the advantages of natural language in tutoring, especially spoken language. SCoT uses a generic architecture for conversational intelligence which has capabilities such as turn management and coordination of multi-modal input and output. SCoT also includes a set of domain independent tutorial recipes, a domain specific production-rule knowledge base, and many natural language components including a bi-directional grammar, a speech recognizer, and a text-to-speech synthesizer. SCoT leads a reflective tutorial discussion based on the details of a problem solving session with a real-time Navy shipboard damage control simulator. The tutor attempts to identify and remediate gaps in the student’s understanding of damage control doctrine by decomposing its tutorial goals into dialogue acts, which are then acted on by the dialogue manager to facilitate the conversation.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
369400070493217927
v2026.09.13