Accession Number:

ADA460937

Title:

Utterance Classification in Auto Tutor

Descriptive Note:

Conference paper

Corporate Author:

MEMPHIS UNIV TN

Report Date:

2003-01-01

Pagination or Media Count:

9.0

Abstract:

This paper describes classification of typed student utterances within AutoTutor, an intelligent tutoring system. Utterances are classified to one of 18 categories including 16 question categories. The classifier presented uses part of speech tagging, cascaded finite state transducers, and simple disambiguation rules. Shallow NLP is well suited to the task session log file analysis reveals significant classification of eleven question categories, frozen expressions, and assertions.

Subject Categories:

  • Information Science
  • Linguistics
  • Computer Systems
  • Humanities and History

Distribution Statement:

APPROVED FOR PUBLIC RELEASE