Many individuals with disabilities use virtual home assistants (VHAs) to communicate and execute daily tasks (Pradhan, Mehta & Findlater 2018). Because VHAs are controlled by verbal communication, some groups of users, including people with speech impairments, face barriers to effective interaction with VHAs. My research addresses the problems that individuals with speech impairments, specifically those with dysarthria, experience in interacting with these devices. I propose an alternate technique for interaction using nonverbal voice cues, such as humming, hissing and vowel sounds. The technique requires from the user only the ability to vocalise.
In recent years, rapid advancements have taken place for automatic speech recognition (ASR) systems and devices. Though ASR technologies have increased, the accessibility of these novel interaction systems is underreported and may present difficulties for people with speech impediments. In this article, we attempt to identify gaps in current research on the interaction between people with dysarthria and ASR systems and devices. We cover the period from 2011, when Siri (the first and the leading commercial voice assistant) was launched, to 2020. The review employs an interaction framework in which each element (user, input, system, and output) contributes to the interaction process. To select the articles for review, we conducted a search of scientific databases and academic journals. A total of 36 studies met the inclusion criteria, which included use of the word error rate (WER) as a measurement for evaluating ASR systems. This review determines that challenges in interacting with ASR systems persist even in light of the most recent commercial technologies. Further, understanding of the entire interaction process remains limited; thus, to improve this interaction, the recent progress of ASR systems must be elucidated.
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