Chrome Extension
WeChat Mini Program
Use on ChatGLM

The Effectiveness of Automatic Speech Recognition in ESL/EFL Pronunciation: A Meta-Analysis

ReCALL(2023)

Cited 1|Views2
No score
Abstract
This meta-analytic study explores the overall effectiveness of automatic speech recognition (ASR) on ESL/EFL student pronunciation performance. Data with 15 studies representing 38 effect sizes found from 2008 to 2021 were meta-analyzed. The findings of the meta-analysis indicated that ASR has a medium overall effect size (g = 0.69). Results from moderator analyses suggest that (1) ASR with explicit corrective feedback is largely effective, while ASR with indirect feedback (e.g. ASR dictation) is moderately effective; (2) ASR has a large effect on segmental pronunciation but a small effect on suprasegmental pronunciation; (3) medium to long treatment duration of ASR results in higher learning outcomes, but short duration offers no differential effect compared to a non-ASR condition; (4) practicing pronunciation with peers in an ASR condition produces a large effect, but the effect is small when practicing alone; (5) ASR is largely effective for adult (i.e. 18 years old and above) and intermediate English learners. Overall, ASR is a beneficial application and is recommended for assisting L2 student pronunciation development.
More
Translated text
Key words
automatic speech recognition,ASR,speech technology,pronunciation,meta-analysis,effectiveness
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined