Classification of Utterances Based on Multiple BLEU Scores for Translation-Game-Type CALL Systems

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Author(s)

    • KUWA Reiko
    • Graduate School of Science and Engineering, Doshisha University
    • KATO Tsuneo
    • Graduate School of Science and Engineering, Doshisha University

Abstract

<p>This paper proposes a classification method of second-language-learner utterances for interactive computer-assisted language learning systems. This classification method uses three types of bilingual evaluation understudy (BLEU) scores as features for a classifier. The three BLEU scores are calculated in accordance with three subsets of a learner corpus divided according to the quality of utterances. For the purpose of overcoming the data-sparseness problem, this classification method uses the BLEU scores calculated using a mixture of word and part-of-speech (POS)-tag sequences converted from word sequences based on a POS-replacement rule according to which words are replaced with POS tags in <i>n</i>-grams. Experiments of classifying English utterances by Japanese demonstrated that the proposed classification method achieved classification accuracy of 78.2% which was 12.3 points higher than a baseline with one BLEU score.</p>

Journal

  • IEICE Transactions on Information and Systems

    IEICE Transactions on Information and Systems E101.D(3), 750-757, 2018

    The Institute of Electronics, Information and Communication Engineers

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