Mispronunciation Detection Using Neural Networks for Second Language Learners

Abstract

Speaking a second language fluently is the aim of any language learner. Computer-aided language learning (CALL) systems help learners achieve this goal. Mispronunciation detection can be considered the most helpful component in CALL systems. For this reason, the focus is currently on research in mispronunciation detection systems. There are different methods for mispronunciation detection, such as posterior probability-based methods and classifier-based methods. Recently, deep-learning-based methods have also attracted great interest and are being studied. This chapter reviews the research that proposed neural network methods for mispronunciation detection conducted between 2014 and 2021 for second language learners. The results obtained from studies in the literature and comparisons between different techniques are also discussed.