The Implementation of Automated Speech Recognition (ASR) in ELT Classroom: A Systematic Literature Review from 2012-2023

Abstract

Automated Speech Recognition (ASR) turns speech audio streams into text. The use of computer-based voice recognition is beneficial for teaching pronunciation. It may also be used to evaluate a learner's speech in a broader context and set up the potential for creating aural interactions between the learner and the computer. The study is aimed to investigate the use of ASR in speaking assessment using a systematic literature review. Automated scores should be considered based on their validity and any potential issues or mistakes with employing technology (ASR) to evaluate speaking. Although some research has been carried out on the use of technology in speaking assessment, there have been few empirical studies using systematic literature reviews to explore more about ASR in education. Therefore, this study is aimed to provide an updated and comprehensive review of the implementation of Automated Speech Recognition (ASR) in education. Ten studies from journals cited in the Taylor Francis, Wiley, and Springer databases were selected.  The results show the benefits of ASR in education including students' progress, interaction, and pedagogical contributions. Pedagogical contributions provide collaboration between the human and automated scores. Teachers can use this study to improve speaking assessments using ASR in the classroom.