A Multi-model SVR Approach to Estimating the CEFR Proficiency Level of Grammar Item Features

Brendan Flanagan, Sachio Hirokawa, Emiko Kaneko, Emi Izumi, Hiroaki Ogata

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Analysis of publicly available language learning corpora can be useful for extracting characteristic features of learners from different proficiency levels. This can then be used to support language learning research and the creation of educational resources. In this paper, we classify the words and parts of speech of transcripts from different speaking proficiency levels found in the NICT-JLE corpus. The characteristic features of learners who have the equivalent spoken proficiency of CEFR levels A1 through to B2 were extracted by analyzing the data with the support vector machine method. In particular, we apply feature selection to find a set of characteristic features that achieve optimal classification performance, which can be used to predict spoken learner proficiency.

    Original languageEnglish
    Title of host publicationProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
    EditorsKiyota Hashimoto, Naoki Fukuta, Tokuro Matsuo, Sachio Hirokawa, Masao Mori, Masao Mori
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages521-526
    Number of pages6
    ISBN (Electronic)9781538606216
    DOIs
    Publication statusPublished - Nov 15 2017
    Event6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 - Hamamatsu, Shizuoka, Japan
    Duration: Jul 9 2017 → …

    Publication series

    NameProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017

    Other

    Other6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
    Country/TerritoryJapan
    CityHamamatsu, Shizuoka
    Period7/9/17 → …

    All Science Journal Classification (ASJC) codes

    • Artificial Intelligence
    • Computer Networks and Communications
    • Computer Science Applications
    • Information Systems
    • Information Systems and Management

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