Predicting Clinical Evaluations of Children’s Speech with Limited Data Using Exemplar Word Template References

Gary Yeung, Amber Afshan, Kaan Ege Ozgun, Canton Kaewtip, Steven M. Lulich, Abeer Alwan


The need for automated speech pathology diagnostic tools for children has increased in recent years. Such tools can help speech pathologists identify speech disorders in children at an early age. This paper introduces an approach to automated clinical evaluations of children's speech using limited data. A database of ten normally developing first-grade children administered the Goldman-Fristoe Test of Articulation, 3rd Edition (GFTA-3) was recorded. Graduate clinicians evaluated the pronunciation of the rhotic sounds by evaluating words in the GFTA-3 containing the letter r. The rhotic sounds were specifically chosen due to their late acquisition in children. Experiments were performed attempting to predict the results of the clinical evaluations. Five children, judged to have proper rhotic pronunciations, were chosen as exemplar templates for the experiment. The remaining children, used for evaluation, were aligned in time to match the five templates using dynamic time warping, and the difference between a test child's r and a template child's r was measured using the cosine distance. Multiple linear regression on the difference scores was shown to be effective at producing predictions that were well-correlated with human clinical evaluations. Several sublists of words with rhotic sounds were used to evaluate the regression, and the sublist containing words with the most mispronunciations performed best. Further discussion includes how much each individual template contributed to the regression and how consistent the clinicians were at scoring children's speech production.


 DOI: 10.21437/SLaTE.2017-28

Cite as: Yeung, G., Afshan, A., Ozgun, K.E., Kaewtip, C., Lulich, S.M., Alwan, A. (2017) Predicting Clinical Evaluations of Children’s Speech with Limited Data Using Exemplar Word Template References. Proc. 7th ISCA Workshop on Speech and Language Technology in Education, 161-166, DOI: 10.21437/SLaTE.2017-28.


@inproceedings{Yeung2017,
  author={Gary Yeung and Amber Afshan and Kaan Ege Ozgun and Canton Kaewtip and Steven M. Lulich and Abeer Alwan},
  title={ Predicting Clinical Evaluations of Children’s Speech with Limited Data Using Exemplar Word Template References},
  year=2017,
  booktitle={Proc. 7th ISCA Workshop on Speech and Language Technology in Education},
  pages={161--166},
  doi={10.21437/SLaTE.2017-28},
  url={http://dx.doi.org/10.21437/SLaTE.2017-28}
}