School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg.
S Afr J Commun Disord. 2022 Aug 19;69(2):e1-e11. doi: 10.4102/sajcd.v69i2.915.
The emergence of the coronavirus disease 2019 (COVID-19) pandemic has resulted in communication being heightened as one of the critical aspects in the implementation of interventions. Delays in the relaying of vital information by policymakers have the potential to be detrimental, especially for the hearing impaired.
This study aims to conduct a scoping review on the application of artificial intelligence (AI) for real-time speech-to-text to sign language translation and consequently propose an AI-based real-time translation solution for South African languages from speech-to-text to sign language.
Electronic bibliographic databases including ScienceDirect, PubMed, Scopus, MEDLINE and ProQuest were searched to identify peer-reviewed publications published in English between 2019 and 2021 that provided evidence on AI-based real-time speech-to-text to sign language translation as a solution for the hearing impaired. This review was done as a precursor to the proposed real-time South African translator.
The review revealed a dearth of evidence on the adoption and/or maximisation of AI and machine learning (ML) as possible solutions for the hearing impaired. There is a clear lag in clinical utilisation and investigation of these technological advances, particularly in the African continent.
Assistive technology that caters specifically for the South African community is essential to ensuring a two-way communication between individuals who can hear clearly and individuals with hearing impairments, thus the proposed solution presented in this article.
2019 年冠状病毒病(COVID-19)大流行的出现导致沟通成为干预措施实施的关键方面之一。政策制定者在传递重要信息方面的延迟可能会产生不利影响,特别是对于听力受损者。
本研究旨在对人工智能(AI)在实时语音到文本的手语翻译中的应用进行范围综述,并随后提出一种基于 AI 的实时翻译解决方案,将南非语言从语音到文本转换为手语。
电子书目数据库,包括 ScienceDirect、PubMed、Scopus、MEDLINE 和 ProQuest,用于检索 2019 年至 2021 年间发表的同行评议的英文出版物,这些出版物提供了有关 AI 实时语音到文本到手语翻译作为听力障碍者解决方案的证据。这项综述是为拟议的实时南非翻译器做准备。
综述显示,关于采用和/或最大化人工智能和机器学习(ML)作为听力障碍者的可能解决方案的证据很少。这些技术进步在临床应用和研究方面明显滞后,特别是在非洲大陆。
专门为南非社区提供的辅助技术对于确保听力正常者和听力受损者之间的双向沟通至关重要,因此本文提出了拟议的解决方案。