Presentation | 2013-10-19 Exploring Linguistic Features for the Automated Assessment of L2 Spoken English Yuichiro KOBAYASHI, Mariko ABE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | The present study aims to automatically evaluate second language (L2) spoken English, and to identify linguistic features for predicting speaking proficiency. It drew on the NICT JLE Corpus, a corpus of 1,281 Japanese EFL learners, coded with speaking proficiency. The oral proficiency levels were used as criterion variable and linguistic features analyzed in Biber (1988) as explanatory variables. Random forests (Breiman, 2001) was employed to predict the speaking proficiency. As a result of random forests with the out-of-bag error estimate, 61.28% of L2 spoken productions were correctly classified. The strongest predictors of an individual's level were tokens, types, prepositions, tense, and first person pronouns. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | L2 Spoken English / Learner Corpus / Machine Learning |
Paper # | TL2013-41 |
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Committee | TL |
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Conference Date | 2013/10/12(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Thought and Language (TL) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Exploring Linguistic Features for the Automated Assessment of L2 Spoken English |
Sub Title (in English) | |
Keyword(1) | L2 Spoken English |
Keyword(2) | Learner Corpus |
Keyword(3) | Machine Learning |
1st Author's Name | Yuichiro KOBAYASHI |
1st Author's Affiliation | Japan Society for the Promotion of Science() |
2nd Author's Name | Mariko ABE |
2nd Author's Affiliation | Faculty of Science and Engineering, Chuo University |
Date | 2013-10-19 |
Paper # | TL2013-41 |
Volume (vol) | vol.113 |
Number (no) | 253 |
Page | pp.pp.- |
#Pages | 6 |
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