Feasibility of Automatic Speech Recognition for Providing Feedback During Tablet-Based Treatment for Apraxia of Speech Plus Aphasia

Author:

Ballard Kirrie J.1,Etter Nicole M.2,Shen Songjia3,Monroe Penelope1,Tien Tan Chek4

Affiliation:

1. Faculty of Health Sciences, University of Sydney, New South Wales, Australia

2. Department of Communication Sciences and Disorders, Pennsylvania State University, University Park

3. Games Studio, University of Technology Sydney, New South Wales, Australia

4. InfoComm Technology Cluster, Singapore Institute of Technology, Singapore

Abstract

Purpose Individuals with neurogenic speech disorders require ongoing therapeutic support to achieve functional communication goals. Alternative methods for service delivery, such as tablet-based speech therapy applications, may help bridge the gap and bring therapeutic interventions to the patient in an engaging way. The purpose of this study was to evaluate an iPad-based speech therapy app that uses automatic speech recognition (ASR) software to provide feedback on speech accuracy to determine the ASR's accuracy against human judgment and whether participants' speech improved with this ASR-based feedback. Method Five participants with apraxia of speech plus aphasia secondary to stroke completed an intensive 4-week at-home therapy program using a novel word training app with built-in ASR. Multiple baselines across participants and behaviors designs were employed, with weekly probes and follow-up at 1 month posttreatment. Four sessions a week of 100 practice trials each were prescribed, with 1 being clinician-run and the remainder done independently. Dependent variables of interest were ASR–human agreement on accuracy during practice trials and human-judged word production accuracy over time in probes. Also, user experience surveys were completed immediately posttreatment. Results ASR–human agreement on accuracy averaged ~80%, which is a common threshold applied for interrater agreement. All participants demonstrated improved word production accuracy over time with the ASR-based feedback and maintenance of gains after 1 month. All participants reported enjoying using the app with support of a speech pathologist. Conclusion For these participants with apraxia of speech plus aphasia due to stroke, satisfactory gains were made in word production accuracy with an app-based therapy program providing ASR-based feedback on accuracy. Findings support further testing of this ASR-based approach as a supplement to clinician-run sessions to assist clients with similar profiles in achieving higher amount and intensity of practice as well as empowering them to manage their own therapy program. Supplemental Material https://doi.org/10.23641/asha.8206628

Publisher

American Speech Language Hearing Association

Subject

Speech and Hearing,Linguistics and Language,Developmental and Educational Psychology,Otorhinolaryngology

Reference50 articles.

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3. Australian Bureau of Statistics. (2011). ABS Canberra. Retrieved from http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/4102.0Main+Features30Mar+2011

4. Australian Government Department of Human Services. (2018). Requested Medicare items processed from July 2016 to June 2017. http://medicarestatistics.humanservices.gov.au/statistics/mbs_item.jsp

5. Optimal intervention intensity

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