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. An AAC-ASR model was developed that transcribes simulated AAC speaker language samples. The AAC-ASR model's word error rate (WER) was compared with those of CMU Sphinx and Google Speech-to-text. The WER of the AAC-ASR model outperformed (28.6%) compared with CMU Sphinx and Google when tested on the testing files (70.7% and 86.2% retrospectively). Our results demonstrate the feasibility of using the ASR model to automatically transcribe high-technology AAC-simulated language samples to support language sample analysis. Future steps will focus on developing the model with diverse AAC speech training datasets and understanding the speech patterns of individual AAC users to refine the AAC-ASR model.

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. However, little evidence has demonstrated the use of AAC intervention (AACT) in early recovery from people with post-stroke aphasia in in-patient rehabilitation settings for improving these patients' communication effectiveness. The pilot randomized controlled trial (RCT) will explore the effectiveness and feasibility of including AACT in regular SLT for in-patient people with post-stroke aphasia. METHOD: This pilot RCT is a single-blind, randomized controlled trial with two parallel groups. Both groups receive a 1-h treatment session, including either both AACT and SLT or SLT only for ten consecutive days. We aim to include 22 in-patient participants with post-stroke aphasia in each group. Participants will be assessed at pre- and post-intervention and 2 weeks after intervention. The primary outcomes are the ability of communication measured by the communication of basic needs subtest in the Functional Assessment of Communication Skills for Adult (FACS) and the overall language performance measured by the Chinese Standard Aphasia Battery (ABC). The secondary outcomes include a 10-min conversation, the 10-item Hospital version of the Stroke Aphasic Depression Questionnaire (SADQH-10), the Stroke-Specific Quality of Life Scale (SS-QOL), and a patient and caregiver satisfaction questionnaire. DISCUSSION: This pilot RCT will contribute to new scientific evidence to the field of aphasia rehabilitation in early recovery during the in-patient period. The paper describes the trial, which will explore the effect of combining AACT and SLT and SLT only, our choice of primary and secondary outcome measures, and proposed analyses. The study results will provide information for implementing AACT in the regular in-patient SLT of future RCTs. TRIAL REGISTRATION: Chinese Clinical Trial Registry database (ChiCTR) ChiCTR2000028870 . Registered on 5 January 2020.

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. OBJECTIVE: The objective of this project was to develop an integrated mobile health Augmentative and Alternative Communication (AAC) platform consisting of an AAC mobile app and a Web-based clinician portal for supporting evidence-based clinical service delivery. METHODS: A questionnaire and interviews were used to collect clinicians' ideas regarding what constitutes their desired "clinically relevant" data. In response, a Web-based portal was designed by combining mobile and Web technologies with an AAC intervention to create an integrated platform for supporting data collection, integration, and reporting. Finally, a usability study was conducted with health care professionals. RESULTS: A Web-based portal was created and integrated with a tablet-based AAC mobile app and data analysis procedures. In the usability study, all participants agreed that the integrated platform provided the ability to collect comprehensive clinical evidence, automatically analyze collected data in real time, and generate clinically relevant performance measures through an easily accessible Web-based portal. CONCLUSIONS: The integrated platform offers a better approach for clinical data reporting and analytics. Additionally, the platform streamlines the workflow of AAC clinical service delivery.

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. Two groups of study participants were recruited to participate a usability study and a preliminary feasibility study for the purpose of evaluating this mobile AAC app, respectively. RESULTS: A tablet-based AAC app was developed to support communication rehabilitation. User studies of the app were conducted and included able-bodied individuals and people with verbal communication disabilities. All study participants agreed that the app establishes a usable alternative treatment protocol for communication rehabilitation. CONCLUSIONS: The app's integrated features have great potential to maximize users' communication effectiveness, enhance language skills, and ultimately improve users' quality of life. Implications for rehabilitation We have developed and evaluated an integrated mobile AAC language-based app. This tablet-based app integrated AAC with embedded trainings and real-time performance report.