Evaluating the Effect of Predicting Oral Reading Miscues - Robotics Institute Carnegie Mellon University

Evaluating the Effect of Predicting Oral Reading Miscues

S. Banerjee, Joseph E. Beck, and Jack Mostow
Conference Paper, Proceedings of 8th European Conference on Speech Communication and Technology (EUROSPEECH '03), pp. 3165 - 3168, September, 2003

Abstract

This paper extends and evaluates previously published methods for predicting likely miscues in children's oral reading in a Reading Tutor that listens. The goal is to improve the speech recognizer's ability to detect miscues but limit the number of "false alarms" (correctly read words misclassified as incorrect). The "rote" method listens for specific miscues from a training corpus. The "extrapolative" method generalizes to predict other miscues on other words. We construct and evaluate a scheme that combines our rote and extrapolative models. This combined approach reduced false alarms by 0.52% absolute (12% relative) while simultaneously improving miscue detection by 1.04% absolute (4.2% relative) over our existing miscue prediction scheme.

BibTeX

@conference{Banerjee-2003-8751,
author = {S. Banerjee and Joseph E. Beck and Jack Mostow},
title = {Evaluating the Effect of Predicting Oral Reading Miscues},
booktitle = {Proceedings of 8th European Conference on Speech Communication and Technology (EUROSPEECH '03)},
year = {2003},
month = {September},
pages = {3165 - 3168},
}