Open Access
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
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]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.