Open Access
Issue
SHS Web Conf.
Volume 102, 2021
The 3rd ETLTC International Conference on Information and Communications Technology (ETLTC2021)
Article Number 01005
Number of page(s) 6
Section Technology Assisted Language Learning
DOI https://doi.org/10.1051/shsconf/202110201005
Published online 03 May 2021
  1. K. Hirabayashi, S. Nakagawa: Automatic evaluation of English pronunciation by Japanese speakers using various acoustic features and pattern recognition techniques. Proc. Interspeech, 598-601 (2010) [Google Scholar]
  2. H. Wang, C.J. Waple, T. Kawahara: Computer assisted language learning system based on dynamic question generation and error prediction for automatic speech recognition. J. Speech Communication, Vol.51, No.10, 995-1005 (2009) [Google Scholar]
  3. S. Nakamura, S. Matsuda, H. Kato, M. Tsuzaki and Y. Sagisaka: Objective evaluation of English learners’ timing control based on a measure reflecting perceptual characteristics. Proc. IEEE ICASSP, 4837-4840 (2009) [Google Scholar]
  4. S. Nakamura, H. Kato and Y. Sagisaka: Effects of Mora-timing in English Rhythm Control by Japanese Learners. Proc. INTERSPEECH 2009 1539-1542 (2009) [Google Scholar]
  5. H. Wang, T. Kawahara: Effective prediction of errors by non-native speakers using decision tree for speech recognition-based CALL system. IEICE Trans., Vol. E92-D, No.12, 2462-2468 (2009) [Google Scholar]
  6. Keiji Yasuda, Eiichiro Sumita, Seiichi Yamamoto, Masuzo Yanagida, Kikuo Maekawa, and Fumiaki Sugaya: A Proposal for Automatically Gauging of English Language Proficiency. IPSJ SIG Technical Report, Vol. 2003-NL-155: 65-70 (2003) [Google Scholar]
  7. Sakata Kosuke, Shimbo Masashi, Matsumoto Yuji: Automatic estimation of English proficiency level using corpora. Information Processing Society of Japan SIG Technical Report 2007-NL-181, 113-119 (2007) [Google Scholar]
  8. Mashael A. Al-Barrak and Muna Al-Razgan: Predicting Students Final GPA Using Decision Trees: A Case Study. International Journal of Information and Education Technology, Vol. 6, No. 7, July 2016, 528-533 (2016) [Google Scholar]
  9. Junko Negishi: Multi-faceted Rasch analysis for the assessment of group oral interaction using CEFR criteria. Annual Review of English Language Education in Japan, 21, 111-120 (2010) [Google Scholar]
  10. Council of Europe: “Common European framework of reference for languages: Learning, teaching, assessment”, Cambridge: Cambridge University Press (2001) [Google Scholar]
  11. Aboagye, E.A. and Mensah Cynthia: Principal Component Analysis of Students’ Academic Performance in Mathematics and Statistics. American Based Research Journal, Vol-5-Issue-10. (2016) [Google Scholar]
  12. M. Arai, T. Hajime, Y. Sagisaka: Principal Component Analysis on English Conversation Data of Japanese L2-Learners. International Workshop of Intelligent Data Analytics and Applications Joint with JSAI International Symposia on AI. (2018) [Google Scholar]

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