Abstract
As an emerging technology for Computer Assisted Pronunciation Training (CAPT), ASR (automatic speech recognition) has been used to improve language learners’ pronunciation and speaking abilities. This study examined the difference in EFL (English as a foreign language) learners’ sound deletion performance with peer feedback and individual practice when using an automatic speech recognition (ASR) system. During each weekend, participants used DingTalk, a software with ASR message to practice reading the passages from their textbooks. The participants marked the mistakes in the ASR by themselves (N = 30) or with feedback from partners (N = 30). The intervention spanned eight weeks. Besides the overall pronunciation performance, the frequency counts of the phoneme and syllable deletion were measured before and after the treatment. The results revealed significant differences in both groups’ overall pronunciation performance, overall sound deletion performance, phoneme and syllable deletion, which showed that the peer feedback group performs better than the self-corrected group. Participants’ attitudes towards the ASR-based pronunciation practice were also investigated in the present study.
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Acknowledgements
This work is supported by the Center for Language Cognition and Assessment, South China Normal University. It’s also the result of Guangdong “13th Five-Year” Plan Project of Philosophy & Social Science (GD20WZX01-02).
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Wu, X., Liu, X., Chen, L. (2021). Reducing EFL Learners’ Error of Sound Deletion with ASR-Based Peer Feedback. In: Jia, W., et al. Emerging Technologies for Education. SETE 2021. Lecture Notes in Computer Science(), vol 13089. Springer, Cham. https://doi.org/10.1007/978-3-030-92836-0_16
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