A proof-of-concept study for automatic speech recognition to transcribe AAC speakers' speech from high-technology AAC systems.

Automatic speech recognition (ASR) is an emerging technology that has been used in recognizing non-typical speech of people with speech impairment and enhancing the language sample transcription process in communication sciences and disorders. However, the feasibility of using ASR for recognizing speech samples from high-tech Augmentative and Alternative Communication (AAC) systems has not been investigated. This proof-of-concept paper aims to investigate the feasibility of using AAC-ASR to transcribe language samples generated by high-tech AAC systems and compares the recognition accuracy of two published ASR models: CMU Sphinx and Google Speech-to-text.

Augmentative and alternative communication intervention for in-patient individuals with post-stroke aphasia: study protocol of a parallel-group, pragmatic randomized controlled trial.

Background: People with post-stroke aphasia commonly receive speech-language therapy (SLT) when they are admitted to hospitals. Commonly, these patients reported communication difficulties in in-patient settings. Augmentative and alternative communication (AAC) has been reported as an effective treatment approach to improve communication effectiveness, language performance, decreasing depression, and improving quality of life for this population.

An mHealth Platform for Supporting Clinical Data Integration into Augmentative and Alternative Communication Service Delivery: User-Centered Design and Usability Evaluation.

Background: The recent trend of increasing health care costs in the United States is likely not sustainable. To make health care more economically sustainable, attention must be directed toward improving the quality while simultaneously reducing the cost of health care. One of the recommended approaches to provide better care at a lower cost is to develop high-quality data collection and reporting systems, which support health care professionals in making optimal clinical decisions based on solid, extensive evidence.

Development and evaluation of a mobile AAC: a virtual therapist and speech assistant for people with communication disabilities.

Purpose: The currently existing Augmentative and Alternative Communication (AAC) technologies have limitations to produce the best communication rehabilitation outcomes and therefore a better solution is needed.

Method: In this work, a mobile AAC app was developed based on results from research studies. Sophisticated AAC language programming, embedded training materials, and real-time communication performance reporting were integrated into the app.