On the Automatic Classification of Reading Disorders

Andreas Maier, Caroline Parchmann, Tobias Bocklet, Florian Hönig, Oliver Kratz, Stefanie Horndasch, Elmar Nöth, Gunther Moll

2009

Abstract

In this paper, we present an automatic classification approach to identify reading disorders in children. This identification is based on a standardized test. In the original setup the test is performed by a human supervisor who measures the reading duration and notes down all reading errors of the child at the same time. In this manner we recorded tests of 38 children who were suspected to have reading disorders. The data was confronted to an automatic system which employs speech recognition to identify the reading errors. In a subsequent classification experiment — based on the speech recognizer’s output and the duration of the test— 94.7% of the children could be classified correctly.

References

  1. I. Dennis and J. St. B. T. Evans, “The speed-error trade-off problem in psychometric testing,” British Journal of Psychology, vol. 87, pp. 105-129, 1996.
  2. M. Black, J. Tepperman, S. Lee, and S. Narayanan, “Estimation of children's reading ability by fusion of automatic pronunciation verification and fluency detection,” in Interspeech 2008 - Proc. Int. Conf. on Spoken Language Processing, 11th International Conference on Spoken Language Processing, September 25-28, 2008, Brisbane, Australia, Proceedings, 2008, pp. 2779-2782.
  3. J. Duchateau, L. Cleuren, H. Van Hamme, and P. Ghesquiere, “Automatic assessment of children's reading level,” in Interspeech 2007 - Proc. Int. Conf. on Spoken Language Processing, 10th European Conference on Spoken Language Processing, August 27-31, 2007, Antwerp, Belgium, Proceedings, 2007, pp. 1210-1213.
  4. A. Maier, T. Haderlein, U. Eysholdt, F. Rosanowski, A. Batliner, M. Schuster, and E. Nöth, “PEAKS - A System for the Automatic Evaluation of Voice and Speech Disorders,” Speech Communication, vol. 51, no. 5, pp. 425-437, 2009.
  5. A. Maier, E. Nöth, A. Batliner, E. Nkenke, and M. Schuster, “Fully Automatic Assessment of Speech of Children with Cleft Lip and Palate,” Informatica, vol. 30, no. 4, pp. 477-482, 2006.
  6. M. Schuster, T. Haderlein, E. Nöth, J. Lohscheller, U. Eysholdt, and F. Rosanowski, “Intelligibility of laryngectomees' substitute speech: automatic speech recognition and subjective rating,” Eur Arch Otorhinolaryngol, vol. 263, no. 2, pp. 188-193, 2006.
  7. M. Windrich, A. Maier, R. Kohler, E.Nöth, E. Nkenke, U. Eysholdt, and M. Schuster, “Automatic Quantification of Speech Intelligibility of Adults with Oral Squamous Cell Carcinoma,” Folia Phoniatr Logop, vol. 60, pp. 151-156, 2008.
  8. K. Landerl, H. Wimmer, and E. Moser, Salzburger Lese- und Rechtschreibtest. Verfahren zur Differentialdiagnose von Störungen des Lesens und des Schreibens für die 1. bis 4. Schulstufe, Huber, Bern, 1997.
  9. F. Gallwitz, Integrated Stochastic Models for Spontaneous Speech Recognition, vol. 6 of Studien zur Mustererkennung, Logos Verlag, Berlin (Germany), 2002.
  10. G. Stemmer, Modeling Variability in Speech Recognition, vol. 19 of Studien zur Mustererkennung, Logos Verlag, Berlin (Germany), 2005.
  11. E.G. Schukat-Talamazzini, H. Niemann, W. Eckert, T. Kuhn, and S. Rieck, “Automatic Speech Recognition without Phonemes,” in Proc. European Conf. on Speech Communication and Technology (Eurospeech), Berlin (Germany), 1993, vol. 1, pp. 129-132.
  12. K. Riedhammer, G. Stemmer, T. Haderlein, M. Schuster, F. Rosanowski, E. Nöth, and A. Maier, “Towards Robust Automatic Evaluation of Pathologic Telephone Speech,” in Proceedings of the Automatic Speech Recognition and Understanding Workshop (ASRU), Kyoto, Japan, 2007, pp. 717-722, IEEE Computer Society Press.
  13. W. Wahlster, Ed., Verbmobil: Foundations of Speech-to-Speech Translation, Springer, Berlin (Germany), 2000.
  14. G. Stemmer, C. Hacker, S. Steidl, and E. Nöth, “Acoustic Normalization of Children's Speech,” in Proc. European Conf. on Speech Communication and Technology, Geneva, Switzerland, 2003, vol. 2, pp. 1313-1316.
  15. M. Gales, D. Pye, and P. Woodland, “Variance compensation within the MLLR framework for robust speech recognition and speaker adaptation,” in Proceedings of the International Conference on Speech Communication and Technology (Interspeech), Philadelphia, USA, 1996, vol. 3, pp. 1832-1835, ISCA.
  16. A. Maier, T. Haderlein, and E. Nöth, “Environmental Adaptation with a Small Data Set of the Target Domain,” in 9th International Conf. on Text, Speech and Dialogue (TSD), P. Sojka, I. Kopec?ek, and K. Pala, Eds., Berlin, Heidelberg, New York, 2006, vol. 4188 of Lecture Notes in Artificial Intelligence, pp. 431-437, Springer.
  17. A. Fawcett, “An introduction to ROC analysis,” Pattern Recognition Letters, vol. 27, pp. 861-874, 2006.
  18. Yoav Freund and Robert E. Schapire, “Experiments with a new boosting algorithm,” in Thirteenth International Conference on Machine Learning, San Francisco, 1996, pp. 148- 156, Morgan Kaufmann.
  19. C. Hacker, T. Cincarek, A. Maier, A. Heßler, and E. Nöth, “Boosting of Prosodic and Pronunciation Features to Detect Mispronunciations of Non-Native Children,” in Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Hawaii, USA, 2007, vol. 4, pp. 197-200, IEEE Computer Society Press.
Download


Paper Citation


in Harvard Style

Maier A., Parchmann C., Bocklet T., Hönig F., Kratz O., Horndasch S., Nöth E. and Moll G. (2009). On the Automatic Classification of Reading Disorders . In Proceedings of the 9th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2009) ISBN 978-989-8111-89-0, pages 18-27. DOI: 10.5220/0002174700180027


in Bibtex Style

@conference{pris09,
author={Andreas Maier and Caroline Parchmann and Tobias Bocklet and Florian Hönig and Oliver Kratz and Stefanie Horndasch and Elmar Nöth and Gunther Moll},
title={On the Automatic Classification of Reading Disorders},
booktitle={Proceedings of the 9th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2009)},
year={2009},
pages={18-27},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002174700180027},
isbn={978-989-8111-89-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2009)
TI - On the Automatic Classification of Reading Disorders
SN - 978-989-8111-89-0
AU - Maier A.
AU - Parchmann C.
AU - Bocklet T.
AU - Hönig F.
AU - Kratz O.
AU - Horndasch S.
AU - Nöth E.
AU - Moll G.
PY - 2009
SP - 18
EP - 27
DO - 10.5220/0002174700180027