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Investigation on e-Learning Status Estimation for New Learners - Classifier Selection on Representative Sample Selection.

, , , , and . IEICE Trans. Inf. Syst., 103-D (4): 905-909 (2020)

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Recognition and verification of English by Japanese students for computer-assisted language learning system., , and . INTERSPEECH, page 1205-1208. ISCA, (2002)Transfer Learning based Non-native Acoustic Modeling for Pronunciation Error Detection., , , and . SLaTE, page 42-46. ISCA, (2017)Practical use of English pronunciation system for Japanese students in the CALL classroom., , and . INTERSPEECH, page 1689-1692. ISCA, (2004)An acoustic approach to fricatives in Japanese and German., and . EUROSPEECH, page 271-274. ISCA, (1993)Modelling of the perception of English sentence stress for computer-assisted language learning., , and . INTERSPEECH, page 175-178. ISCA, (2000)Prototyping a call system for students of Japanese using dynamic diagram generation and interactive hints., , , and . INTERSPEECH, ISCA, (2006)Difficulties in Perception and Pronunciation of Mandarin Chinese Disyllabic Word Tone Acquisition: A Study of Some Japanese University Students., , and . PACLIC, National Chengchi University, Taiwan, (2013)Pronunciation error detection using DNN articulatory model based on multi-lingual and multi-task learning., , , and . ISCSLP, page 1-5. IEEE, (2016)Sustaining Outside-of-Class CALL Activities by Means of a Student Self-Evaluation System in a University Blended Learning EFL Course., , , , , and . HCI (15), volume 8524 of Lecture Notes in Computer Science, page 146-154. Springer, (2014)English Speech Database Read by Japanese Learners for CALL System Development., , , , , , and . LREC, European Language Resources Association, (2002)