Abstract:

Interaction of humans and machines has become an integral part of our daily lives on various levels. The benefits of artificial intelligence spark interest for foreign and second language learning. In the current global situation, which has challenged the traditional approaches to language learning, teachers face the challenge to find such tools which will improve communicative skills of their learners in distant learning and partially or fully substitute their physical presence. Pronunciation is a layer of language which can greatly benefit from the support of artificial intelligence (AI) in its training. Automatic speech recognition (ASR) provides a wide range of possibilities in their use in language learning, including providing feedback to learners and evaluation of their performance.

The aim of the study is to provide an overview of the recent practices in practical usage of ASR in pronunciation training by meta-analysis of ten research studies published in the past ten years in academic journals. In the conclusion, the study provides implications for using ARS in ELT classrooms.

The paper presents partial results of the project KEGA 001TTU-4/2019 Higher education of non-native teachers of foreign languages in national and international contexts: needs of non-native teachers of foreign languages in international research context.

Keywords:

ELT, EFL, pronunciation, artificial intelligence, automatic speech recognition.