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- W4287964946 abstract "AbstractVocabulary is essential for second language learners to read documents. Prior studies on vocabulary size estimation, especially in applied linguistics, have been based on the naive assumption that language learners acquire words based on the frequency of balanced corpora. As this assumption is often invalid, vocabulary size estimates have been somewhat inaccurate for educational use. Therefore, this study proposes a novel method for the distributional and more informative estimation of second language vocabulary size from vocabulary test results. To this end, our method makes personalized binary estimations regarding whether a learner knows a word, followed by aggregating the estimation results for many words for a learner. Experimental results using large vocabulary tests showed that our methods provided distributional and more informative estimations compared with baseline methods.KeywordsDistributional estimationVocabulary sizeSecond language vocabulary" @default.
- W4287964946 created "2022-07-26" @default.
- W4287964946 creator A5007171156 @default.
- W4287964946 date "2022-01-01" @default.
- W4287964946 modified "2023-09-29" @default.
- W4287964946 title "Distributional Estimation of Personalized Second-Language Vocabulary Sizes with Wordlists that the Learner is Likely to Know" @default.
- W4287964946 cites W3007483534 @default.
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- W4287964946 doi "https://doi.org/10.1007/978-3-031-11647-6_110" @default.
- W4287964946 hasPublicationYear "2022" @default.
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