Training a Confidence Measure for a Reading Tutor that Listens
Conference Paper, Proceedings of 8th European Conference on Speech Communication and Technology (EUROSPEECH '03), pp. 3161 - 3164, September, 2003
Abstract
One issue in a Reading Tutor that listens is to determine which words the student read correctly. We describe a confidence measure that uses a variety of features to estimate the probability that a word was read correctly. We trained two decision tree classifiers. The first classifier tries to fix insertion and substitution errors made by the speech decoder, while the second classifier tries to fix deletion errors. By applying the two classifiers together, we achieved a relative reduction in false alarm rate by 25.89% while holding the miscue detection rate constant.
BibTeX
@conference{Tam-2003-8752,author = {Y.-C. Tam and Joseph E. Beck and Jack Mostow and S. Banerjee},
title = {Training a Confidence Measure for a Reading Tutor that Listens},
booktitle = {Proceedings of 8th European Conference on Speech Communication and Technology (EUROSPEECH '03)},
year = {2003},
month = {September},
pages = {3161 - 3164},
}
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