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ISCA International Workshop on Speech and Language Technology in Education (SLaTE 2011)Venice, Italy |
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ISCA International Workshop on Speech and Language Technology in Education (SLaTE 2011)Venice, Italy |
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One important feature of automatic reading tutors is their ability
to detect miscues in order to provide feedback to the student
and/or to automatically evaluate the student’s reading proficiency.
The focus of this paper is on improving accuracy of
detecting miscues in dyslexic read speech. We present a miscue
detection method that combines a specialized language model
and the goodness of pronunciation (GOP) score. The language
model is augmented with a subset of the real word substitutions
that are observed in the training set. Experiments have been
conducted on a corpus containing adult dyslexic read speech.
At a miscue detection rate of 34% the false rejection rate (FRR)
using only the specialized language model is 2.6%, for the GOP
score it’s 3.4%, whereas for a combination of the two miscue
detection methods the FRR is only 1.8%, which is a 31% relative
improvement of FRR when compared to the specialized
language model method.
Index Terms. miscue detection, automatic reading tutor,
dyslexia, read speech
Bibliographic reference. Rasmussen, Morten Højfeldt / Lindberg, Børge / Tan, Zheng-Hua (2011): "Combining acoustic and language model miscue detection methods for adult dyslexic read speech", In SLaTE-2011, 21-24.