Presentation

Human and Automated Assessments of Children’s Pronunciation

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Abstract

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. In J. M. Levis, M. Duris, S. Sonsaat-Hegelheimer, & I. Na (Eds.), Proceedings of the 15th Pronunciation in Second Language Learning and Teaching Conference (pp. 1-16). Iowa State University, September 2024. https://doi.org/10.31274/psllt.18696