Graduation Year
2018
Document Type
Thesis
Degree
M.S.
Degree Name
Master of Science (M.S.)
Degree Granting Department
Communication Sciences and Disorders
Major Professor
Michelle Bourgeois, Ph.D.
Committee Member
Alexandra Brandimore, Ph.D.
Committee Member
Robert M. Barker, Ph.D.
Keywords
Alexa, ALS, Amazon Echo, Dysarthria, Speech intelligibility, Speech Recognition
Abstract
There is an ever-growing and increasing amount of technology options that use speech recognition software. Currently, the market includes smartphones, computers, and individual smart home personal assistants that allow for hands-free access to this technology. Research studies have explored the utility of these assistive devices for the completion of activities of daily living; however, there is limited research looking at the accuracy of voice recognition software within smart home personal assistants in populations with disordered speech. In persons with amyotrophic lateral sclerosis (ALS), symptoms include changes to motor functions, speech in particular, and it is unknown how some of these devices may respond to their disordered speech. The present study aimed to examine the accuracy of the Amazon Echo to respond appropriately to commands given by dysarthric patients with ALS. Participants were asked to read a variety of commands to an Amazon Echo. The sentences and responses by the Amazon Echo were audio-recorded for transcription and intelligibility ratings, which were then analyzed to look for relationships between intelligibility, auditory-perceptual features of speech, and sentence type. Results revealed there was no significant relationship between command intelligibility and accuracy of response by the Amazon Echo, nor was there a significant relationship between any of the auditory-perceptual ratings and accuracy of response. There was, however, a significant and positive association between conversational intelligibility and accuracy of responses by the Amazon Echo. This study provides support for use of hands-free assistive technology in patients with ALS to aid in the maintenance of quality of life and activities of daily living.
Scholar Commons Citation
Layden, Caroline A., "Relationship Between Intelligibility and Response Accuracy of the Amazon Echo in Individuals with Amyotrophic Lateral Sclerosis Exhibiting Mild-Moderate Dysarthria" (2018). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/7325
