Probability Distribution of Dependency Distance Based on a Treebank of Japanese EFL Learners’ Interlanguage

ABSTRACT Ouyang and Jiang (2018) measured the second language proficiency of English as a foreign language (EFL) learners based on the probability distribution of dependency distance. However, the typological features of the native language (Chinese) and the target language (English) they adopted are generally considered similar in word order and dependency direction. In addition, their method of classifying the learners’ proficiency levels is based on the learners’ grades, which might weaken the validity of the results. These results are strengthened and verified further in the current research by analysing a treebank of Japanese EFL learners’ interlanguage since their native language and the target language are typologically distinctive. Moreover, the TOEIC score was used as a benchmark to classify the second language proficiency levels of the learners. We found that (1) the mean dependency distance can measure the syntactic complexity of Japanese EFL learners’ interlanguage; (2) constrained by human working memory, the probability distribution of dependency distance based on Japanese EFL learners’ interlanguage follows certain distribution patterns as unveiled in other natural human languages; (3) the parameters of the right truncated modified Zipf-Alekseev distribution can well reflect the changes of the Japanese EFL learners’ second language proficiency, indicating the development of interlanguage.