Document Type

Article

Publication Date

2026

DOI

10.31224/6608

Publication Title

engrXiv

Pages

1-16

Abstract

Apraxia of Speech (AOS) is a motor speech disorder that significantly limits communication and requires intensive, long-term therapy. Access to consistent treatment is often constrained by shortages of speech-language pathologists, high costs, and limited opportunities for continuous monitoring outside clinical settings. Recent advances in Artificial Intelligence (AI) provide new opportunities to support scalable and personalized speech therapy.

This paper presents AURA (Adaptive Understanding and Relearning Assistant for Apraxia), a multimodal AI framework designed to support speech therapy, progress monitoring, and communication for individuals with AOS. The system integrates speech analysis, machine learning–based error detection, reinforcement learning for adaptive therapy, and multimodal Augmentative and Alternative Communication (AAC) support. An initial research prototype has been developed to demonstrate the feasibility of the proposed architecture and workflow. We describe the system architecture, its alignment with evidence-based motor learning principles, and a phased evaluation plan involving expert review, simulated testing, and pilot studies. The proposed framework aims to improve therapy accessibility, engagement, and data-driven intervention for individuals with AOS.

Rights

© 2026 Omotayo Omoyemi, Dr. Rachel K. Johnson.

This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.

Comments

This article is a preprint. It has not undergone peer review.

Original Publication Citation

Omoyemi, O., & Johnson, R. K. (2026). AURA: An AI-powered multimodal prototype for adaptive apraxia of speech therapy and communication support. engrXiv. https://doi.org/10.31224/6608

ORCID

0000-0003-2479-2965 (Johnson)

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