Automatic Speech Recognition in L2 Learning: A Review Based on PRISMA Methodology

Abstract

The language learning field is not exempt from benefiting from the most recent techniques that have revolutionised the field of speech technologies. L2 learning, especially when it comes to learning some of the most spoken languages in the world, is increasingly including more and more automated methods to assess linguistics aspects and provide feedback to learners, especially on pronunciation issues. On the one hand, only a few of these systems integrate automatic speech recognition as a helping tool for pronunciation assessment. On the other hand, most of the computer-assisted language pronunciation tools focus on the segmental level of the language, providing feedback on specific phonetic pronunciation, and disregarding the suprasegmental features based on intonation, among others. The current review, based on the PRISMA methodology for systematic reviews, overviews the existing tools for L2 learning, classifying them in terms of the assessment level, (grammatical, lexical, phonetic, and prosodic), and trying the explain why so few tools are nowadays dedicated to evaluate the intonational aspect. Moreover, the review also addresses the existing commercial systems, as well as the existing gap between those tools and the research developed in this area. Finally, the manuscript finishes with a discussion of the main findings and foresees future lines of research.

Can L2 Pronunciation Be Evaluated without Reference to a Native Model? Pillai Scores for the Intrinsic Evaluation of L2 Vowels

“…The search for objective measures for L2 pronunciation assessment is obviously also relevant within the field of speech technologies. Recent advances in this domain, and particularly in automatic speech recognition (ASR), have driven the development of L2 pronunciation automatic assessment systems, as well as computer-assisted pronunciation training systems (CAPT) (see Xi 2010;Farrús 2023). Automatic assessment of L2 pronunciation is usually performed by statistical models built on top of exclusively or preponderantly native speech.…”

“…97-98). For a recent and thorough literature review on the use of ASR for computer-assisted pronunciation training, see Farrús (2023).…”