aceNovel Approaches to Language Assessment Part 1: Artificial Intelligence-Automated Scoring of a Sentence Recall Task for School-Age Children
Purpose Artificial intelligence (AI) technologies have the potential to enhance the delivery of speech-language pathology services. One area of practice that could benefit from AI is automated screenings for developmental language disorder (DLD) in early elementary students. This report presents the elements and processes involved in evaluating an AI-based automated scoring system using archival recordings. Method A total of 947 audio samples of children completing the Redmond Sentence Recall (RSR) task, represe…
An AI scoring pipeline for the Redmond Sentence Recall task matched the reference standard more closely than human-scored protocols and showed sensitivity of .768 to .873 for identifying DLD.
The system showed some mismatches with human evaluators and tended to produce lower scores, and the reference-standard comparison covered only a 130-child subset of the 947 samples.
Evidence
- Peer-reviewedLanguage, Speech, and Hearing Services in Schools2026-10-09
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Truvace Impact Record TRV-2026-1593, v1: “Novel Approaches to Language Assessment Part 1: Artificial Intelligence-Automated Scoring of a Sentence Recall Task for School-Age Children.” Truvace, 2026-10-16. /record/TRV-2026-1593 (accessed at citation time). sha256 d6c3a3fd06145b45…
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