Automated Speech Recognition in language learning: Potential models, benefits and impact


The study considers Automated Speech Recognition (ASR) in language learning arguing that speech recognition has reached a level of accuracy where it is powering automatic translation and testing. The author considers the impact of ASR technology on language teaching, describes the process of the development of appropriate pedagogical models, and explains how to prepare teachers for their application. The study will give a critical analysis of the pedagogical uses and dangers of ASR technology and address how ASR can be used to automate language assessment.

KEYWORDS: Automated Speech Recognition, ASR, ELT, speech-to-speech translation, translation software, speech synthesis, automated assessment

MICHAEL CARRIER. CEO of Highdale Consulting, consults for a number of educational organisations. Has worked in language education for 30 years as a teacher, trainer, author, and director. Lectures worldwide. Formerly Director, English Language Innovation at the British Council in London, CEO of International House world schools network and Executive Director of Eurocentres USA. Focuses on teacher development, intercultural awareness, and the application of digital technology to education. Has published a number of articles and textbooks and most recently co-edited Digital Language Learning. He has written a number of ELT coursebooks and skills books, including the Front Page series, Business Circles, Intermediate Writing Skills and Spotlight Readers.

More articles in this issue: