Improving Articulation via AI‑Assisted Speech Practice in Children: A Randomized Controlled Pilot Trial (Preprint)

<sec> <title>UNSTRUCTURED</title> <p>Abstract Background: Speech sound disorders are common in childhood, particularly for later‑developing phonemes such as /s/ and /r/. Artificial intelligence (AI)–assisted speech practice tools may increase treatment intensity and provide structured home practice, but controlled evidence in teletherapy contexts remains limited. Objective: To evaluate whether integrating an AI‑assisted speech practice tool with traditional teletherapy improves articulation accuracy of /s/ and /r/ sounds in children aged 6–17 years. Methods: Twenty‑three participants were randomized 1:1 to receive either traditional teletherapy plus AI‑supported home practice (n=12) or traditional teletherapy alone (n=11). All participants completed eight clinician‑led teletherapy sessions. Articulation accuracy was assessed at baseline and post‑intervention using standardized word lists scored by licensed speech‑language pathologists. Results: Participants receiving AI‑assisted practice demonstrated greater mean improvement (35.8%, SD 22.9) than those receiving teletherapy alone (27.5%, SD 22.4). The between‑group difference was 8.4 percentage points (95% CI –11.3 to 28.1), t(21)=0.89, P=.39. The effect size was moderate (Hedges g=0.36). The pilot was underpowered to detect statistical significance. Conclusions: Although not statistically significant, the direction and magnitude of the effect suggest that AI‑assisted practice may enhance articulation outcomes when combined with teletherapy. Larger, prospectively registered trials with blinded scoring are warranted. Trial Registration: Not applicable (pilot trial).</p> </sec>