Presentation
Authors: Mackenzie Novotny (Iowa State University) , Carolyn Richie (Iowa State University) , John M Levis (Iowa State University) , Evgeny Chukharev (Iowa State University)
Assessing children's pronunciation presents a different set of challenges than assessing adults' language. Patterns of errors in children's speech are highly variable, and sources of the errors may be because of developmental stage, speech sound disorders, and language learning status. In school settings, different professionals work with children depending on their needs, including Speech-Language Pathology (SLP) professionals and English as a Second Language (ESL) teachers. Computers, on the other hand, can be trained to identify a wide array of patterns quite quickly. As part of a larger project to create an automated pronunciation diagnostic test for children, we created a test for children 5-7 years old and compared automatic evaluations of 26 children's pronunciation to human evaluations. While the human evaluations showed high agreement, the automatic mispronunciation detection system was inconsistent in its evaluations, making pattern detection for pronunciation screening impossible. We suggest the development of specialized pronunciation detection systems.
Keywords: Children; Pronunciation; Automated assessment; mispronunciation detection; ELL; SLP
How to Cite: Novotny, M. , Richie, C. , Levis, J. M. & Chukharev, E. (2025) “Human and Automated Assessments of Children's Pronunciation”, Pronunciation in Second Language Learning and Teaching Proceedings. 15(1). doi: https://doi.org/10.31274/psllt.18696
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