Harnessing automatic speech recognition to realise Sustainable Development Goals 3, 9, and 17 through interdisciplinary partnerships for children with communication disability

Elise Baker; Weicong Li; Rosemary Hodges; Sarah Masso; Caroline Jones; Yi Guo; Mary Alt; Mark Antoniou; Saeed Afshar; Katrina Tosi; Natalie Munro

doi:10.1080/17549507.2022.2146194

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Harnessing automatic speech recognition to realise Sustainable Development Goals 3, 9, and 17 through interdisciplinary partnerships for children with communication disability

Journal article

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Harnessing automatic speech recognition to realise Sustainable Development Goals 3, 9, and 17 through interdisciplinary partnerships for children with communication disability

Elise Baker, Weicong Li, Rosemary Hodges, Sarah Masso, Caroline Jones, Yi Guo, Mary Alt, Mark Antoniou, Saeed Afshar, Katrina Tosi, …

International journal of speech language pathology, Vol.25(1), pp.125-129

02/01/2023

DOI: https://doi.org/10.1080/17549507.2022.2146194

PMID: 36511655

Appears in Recent Faculty of Health Publications

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UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

Abstract

assessment

automatic speech recognition (ASR)

communication disability

good health and well-being (SDG 3)

industry, innovation and infrastructure (SDG 9)

partnerships for the goals (SDG 17)

Sustainable Development Goals (SDGs)

therapy

Purpose To showcase how applications of automatic speech recognition (ASR) technology could help solve challenges in speech-language pathology practice with children with communication disability, and contribute to the realisation of the Sustainable Development Goals (SDGs). Result ASR technologies have been developed to address the need for equitable, efficient, and accurate assessment and diagnosis of communication disability in children by automating the transcription and analysis of speech and language samples and supporting dual-language assessment of bilingual children. ASR tools can automate the measurement of and help optimise intervention fidelity. ASR tools can also be used by children to engage in independent speech production practice without relying on feedback from speech-language pathologists (SLPs), thus bridging the long-standing gap between recommended and received intervention intensity. These innovative technologies and tools have been generated from interdisciplinary partnerships between SLPs, engineers, data scientists, and linguists. Conclusion To advance equitable, efficient, and effective speech-language pathology services for children with communication disability, SLPs would benefit from integrating ASR solutions into their clinical practice. Ongoing interdisciplinary research is needed to further advance ASR technologies to optimise children’s outcomes. This commentary paper focusses on industry, innovation and infrastructure (SDG 9) and partnerships for the goals (SDG 17). It also addresses SDG 1, SDG 3, SDG 4, SDG 8, SDG 10, SDG 11, and SDG 16.

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Title: Harnessing automatic speech recognition to realise Sustainable Development Goals 3, 9, and 17 through interdisciplinary partnerships for children with communication disability
Creators: Elise Baker - Western Sydney University
Weicong Li - Western Sydney University
Rosemary Hodges - Western Sydney University
Sarah Masso - University of Sydney
Caroline Jones - Western Sydney University
Yi Guo - Western Sydney University
Mary Alt - University of Arizona
Mark Antoniou - Western Sydney University
Saeed Afshar - Western Sydney University
Katrina Tosi - South Western Sydney Local Health District
Natalie Munro - University of Sydney
Publication Details: International journal of speech language pathology, Vol.25(1), pp.125-129
Publisher: Taylor & Francis
Identifiers: 991013169394602368
Copyright: (c) Published by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons. org/licenses/by-nc-nd/4.0/).
Academic Unit: Faculty of Health
Language: English
Resource Type: Journal article

Harnessing automatic speech recognition to realise Sustainable Development Goals 3, 9, and 17 through interdisciplinary partnerships for children with communication disability

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UN Sustainable Development Goals (SDGs)

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