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Corrective Feedback Accuracy and Pronunciation Improvement: Feedback That Is 'Good Enough'
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Alif Silpachai; Reza Neiriz; MacKenzie Novotny; Ricardo Gutierrez-Osuna; John M. Levis; Evgeny Chukharev – Language Learning & Technology, 2024
It is unclear whether corrective feedback (CF) provided by L2 computer-assisted pronunciation training (CAPT) tools must be 100% accurate to promote an acceptable level of improvement in pronunciation. Using a web-based interface, 30 native speakers of Chinese completed a pretest, a computer-based training session to produce nine sound contrasts…
Descriptors: College Students, Foreign Students, English (Second Language), Second Language Instruction
Computer-Assisted Pronunciation Training for Foreign Language Learning of Grammatical Features
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Elsayed Issa; Gus Hahn-Powell – Language Learning & Technology, 2025
This study investigates the effectiveness of a computer-assisted pronunciation training (CAPT) system on second language learners' acquisition of three grammatical features. It presents a CAPT system on top of a phoneme-based, fine-tuned speech recognition model, and is intended to deliver explicit, corrective feedback on the pronunciation of the…
Descriptors: Grammar, Computer Assisted Instruction, Arabic, Second Language Instruction
Restructuring Multimodal Corrective Feedback through Augmented Reality (AR)-Enabled Videoconferencing in L2 Pronunciation Teaching
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Yiran Wen; Jian Li; Hongkang Xu; Hanwen Hu – Language Learning & Technology, 2023
The problem of cognitive overload is particularly pertinent in multimedia L2 classroom corrective feedback (CF), which involves rich communicative tools to help the class to notice the mismatch between the target input and learners' pronunciation. Based on multimedia design principles, this study developed a new multimodal CF model through…
Descriptors: Error Correction, Videoconferencing, Second Language Learning, Second Language Instruction
Using Automatic Speech Processing for Foreign Language Pronunciation Tutor: Some Issues and a Prototype.
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Eskenazi, Maxine – Language Learning & Technology, 1999
Discusses the possible use of automatic speech recognition (ASR) for training students to improve their accents in a foreign language. Principles of good language training as well as the limits of the use of ASR and how to deal with them are discussed, and an example from the Carnegie Mellon FLUENCY system is used to show how such a system may…
Descriptors: Error Correction, Feedback, Higher Education, Language Processing