Examining the effectiveness of integrating corpus-based and AI approaches for English speaking practice

Abstract This study developed and evaluated an online English speaking training approach that integrates corpora and artificial intelligence (AI) tools. The training integrated a self-developed spoken corpus, generative AI tools, and text-to-speech AI tools. Pre- and post-test results identified improvements in participants’ speaking performances. Participants attempted to use more positive linguistic features (e.g. producing complex sentences more frequently) and avoid using negative linguistic features (e.g. reducing the number of vowel errors) after receiving the training. Participants showed positive attitudes towards this corpus-based and AI-integrated English oral ability learning approach and affirmed the importance of integrating both tools. The corpus helped raise participants’ awareness of features that influence speaking performance and offered prompt engineering and feedback-checking functions, while the generative AI tools provided useful feedback and tailor-made sample responses. Additionally, text-to-speech AI tools offered learners with tailor-made native speaker samples for imitation and helped learners learn pausing. Results also revealed that this approach helped create an interactive oral ability learning environment, and the combination of corpora and AI tools provided more accurate feedback for each subskill of speaking.

Authors

Institutions

Publication Details

Journal
ReCALL
Published
2025-12-01
DOI
https://doi.org/10.1017/s0958344025100372
Primary Topic
Second Language Acquisition and Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Examining the effectiveness of integrating corpus-based and AI approaches for English speaking practice

Jing Xuan Tian, Xiaona Zhou, Hsueh Chu Chen
ReCALL
Second Language Acquisition and Learning
article

Examining the effectiveness of integrating corpus-based and AI approaches for English speaking practice

Jing Xuan Tian, Xiaona Zhou, Hsueh Chu Chen
article en

Abstract

Abstract This study developed and evaluated an online English speaking training approach that integrates corpora and artificial intelligence (AI) tools. The training integrated a self-developed spoken corpus, generative AI tools, and text-to-speech AI tools. Pre- and post-test results identified improvements in participants’ speaking performances. Participants attempted to use more positive linguistic features (e.g. producing complex sentences more frequently) and avoid using negative linguistic features (e.g. reducing the number of vowel errors) after receiving the training. Participants showed positive attitudes towards this corpus-based and AI-integrated English oral ability learning approach and affirmed the importance of integrating both tools. The corpus helped raise participants’ awareness of features that influence speaking performance and offered prompt engineering and feedback-checking functions, while the generative AI tools provided useful feedback and tailor-made sample responses. Additionally, text-to-speech AI tools offered learners with tailor-made native speaker samples for imitation and helped learners learn pausing. Results also revealed that this approach helped create an interactive oral ability learning environment, and the combination of corpora and AI tools provided more accurate feedback for each subskill of speaking.

ReCALL
Education University of Hong Kong (HK)
Openalex Percentile: Top 59%
Second Language Acquisition and Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Examining the effectiveness of integrating corpus-based and AI approaches for English speaking practice — Jing Xuan Tian, Xiaona Zhou, et al. · ReCALL (2025) | TGRS Research Map | TGRS