corpus-based-learning
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- PaperReCALL1 Dec 2025
Examining the effectiveness of integrating corpus-based and AI approaches for English speaking practice
Hsueh Chu Chen, Xiaona Zhou, Jing Xuan Tian
An online English speaking training approach integrating a self-developed spoken corpus, generative AI, and text-to-speech tools was developed and evaluated. Pre- and post-tests showed improvements in speaking performance, with participants using more complex sentences and reducing vowel errors. The combination of corpus and AI tools provided accurate feedback and created an interactive learning environment.
Original 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.