An automatic version of a reading disorder test

Authors:
Andreas Maier;Flonan Hönig;Stefan Steidl;Elmar Nöth;Stefanie Horndasch;Elisabeth Sauerhöfer;Oliver Kratz;Gunther Moll
Affiliations:
Universität Erlangen-Nürnberg, Germany;Universität Erlangen-Nürnberg, Germany;Universität Erlangen-Nürnberg, Germany;Universität Erlangen-Nürnberg, Germany;Universitätsklinikum Erlangen;Universitätsklinikum Erlangen;Universitätsklinikum Erlangen;Universitätsklinikum Erlangen
Venue:
ACM Transactions on Speech and Language Processing (TSLP)
Year:
2011

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Abstract

We present a novel system to automatically diagnose reading disorders. The system is based on a speech recognition engine with a module for prosodic analysis. The reading disorder test is based on eight different subtests. In each of the subtests, the system achieves a recognition accuracy of at least 95%. As in the perceptual version of the test, the results of the subtests are then joined into a final test result to determine whether the child has a reading disorder. In the final classification stage, the system identifies 98.3% of the 120 children correctly. In the future, our system will facilitate the clinical evaluation of reading disorders.