A Korean Learner Corpus and Its Features
In this paper, we present a Korean learner corpus and aim to find features to characterize this corpus. The corpus is based on an open writing test of Korean learners (beginners, intermediate and advanced students) with various topics and were manually evaluated and scored. We explore several types...
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| Published in | EONEOHAG no. 75; pp. 69 - 85 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
사단법인 한국언어학회
01.08.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1225-7494 2508-4429 |
| DOI | 10.17290/jlsk.2016..75.69 |
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| Abstract | In this paper, we present a Korean learner corpus and aim to find features to characterize this corpus. The corpus is based on an open writing test of Korean learners (beginners, intermediate and advanced students) with various topics and were manually evaluated and scored. We explore several types of features in the learner corpus by starting with the pre-processing of Korean sentences. Some features are automatically measured using parts of speech tagging which concerns the number of tokens and the correct use of Functional morphemes. Syntax-related features and topic-related features are measured while using the automatic syntactic parsing and statistical language models. These features can be used for language proficiency identification and other learner corpus related applications that make use of machine learning techniques. KCI Citation Count: 0 |
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| AbstractList | In this paper, we present a Korean learner corpus and aim to find features to characterize this corpus. The corpus is based on an open writing test of Korean learners (beginners, intermediate and advanced students) with various topics and were manually evaluated and scored. We explore several types of features in the learner corpus by starting with the pre-processing of Korean sentences. Some features are automatically measured using parts of speech tagging which concerns the number of tokens and the correct use of Functional morphemes. Syntax-related features and topic-related features are measured while using the automatic syntactic parsing and statistical language models. These features can be used for language proficiency identification and other learner corpus related applications that make use of machine learning techniques. KCI Citation Count: 0 |
| Author | Jungyeul Park(박정열) Jung Hee Lee(이정희) |
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| References | Lee, S.-H (REF041830209); 26 |
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| Title | A Korean Learner Corpus and Its Features |
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