This paper is in the following e-collection/theme issue:

Artificial Intelligence (2129) Clinical Information and Decision Making (1915) mHealth for Data Collection and Research (1196) Development and Evaluation of Research Methods, Instruments and Tools (744) Developmental Problems (80) mHealth for Screening (296) Speech-Language Therapy (31)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60520, first published .
Usefulness of Automatic Speech Recognition Assessment of Children With Speech Sound Disorders: Validation Study

Usefulness of Automatic Speech Recognition Assessment of Children With Speech Sound Disorders: Validation Study

Usefulness of Automatic Speech Recognition Assessment of Children With Speech Sound Disorders: Validation Study

Authors of this article:

Do Hyung Kim1 Author Orcid Image ;   Joo Won Jeong1 Author Orcid Image ;   Dayoung Kang1 Author Orcid Image ;   Taekyung Ahn2, 3 Author Orcid Image ;   Yeonjung Hong3 Author Orcid Image ;   Younggon Im3 Author Orcid Image ;   Jaewon Kim1 Author Orcid Image ;   Min Jung Kim4 Author Orcid Image ;   Dae-Hyun Jang1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Rakhimova D, Duisenbekkyzy Z, Adali E. Investigation of ASR Models for Low-Resource Kazakh Child Speech: Corpus Development, Model Adaptation, and Evaluation. Applied Sciences 2025;15(16):8989 View

Conference Proceedings

  1. Duisenbekkyzy Z, Rakhimova D, Yessirkepova A, Adalı E. 2025 10th International Conference on Computer Science and Engineering (UBMK). Fine-Tuning Neural ASR Models for Low-Resource Kazakh Children’s Speech with Preprocessing Enhancements View