Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Interaction between people with dysarthria and speech recognition systems: A review

Jaddoh, Aisha, Loizides, Fernando ORCID: https://orcid.org/0000-0003-0531-6760 and Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646 2022. Interaction between people with dysarthria and speech recognition systems: A review. Assistive Technology: The Offical Journal of RESNA 10.1080/10400435.2022.2061085
Item availability restricted.

[thumbnail of asstech.pdf] PDF - Accepted Post-Print Version
Restricted to Repository staff only until 18 April 2023 due to copyright restrictions.
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (352kB)

Abstract

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.

Item Type: Article
Date Type: Published Online
Status: In Press
Schools: Computer Science & Informatics
Publisher: Taylor & Francis
ISSN: 1040-0435
Date of First Compliant Deposit: 31 March 2022
Date of Acceptance: 28 March 2022
Last Modified: 25 Jan 2023 14:17
URI: https://orca.cardiff.ac.uk/id/eprint/148933

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics