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Rule-based and machine learning approaches for second language sentence-level readability
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- Pilán, Ildikó, 1985 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för svenska språket,Department of Swedish
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- Volodina, Elena, 1973 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för svenska språket,Department of Swedish
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- Johansson, Richard, 1975 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för svenska språket,Department of Swedish
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(creator_code:org_t)
- 2014
- 2014
- English.
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In: Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications, June 26, 2014 Baltimore, Maryland, USA. - 9781941643037
- Related links:
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https://gup.ub.gu.se...
Abstract
Subject headings
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- We present approaches for the identification of sentences understandable by second language learners of Swedish, which can be used in automatically generated exercises based on corpora. In this work we merged methods and knowledge from machine learning-based readability research, from rule-based studies of Good Dictionary Examples and from second language learning syllabuses. The proposed selection methods have also been implemented as a module in a free web-based language learning platform. Users can use different parameters and linguistic filters to personalize their sentence search with or without a machine learning component assessing readability. The sentences selected have already found practical use as multiple-choice exercise items within the same platform. Out of a number of deep linguistic indicators explored, we found mainly lexical-morphological and semantic features informative for second language sentence-level readability. We obtained a readability classification accuracy result of 71%, which approaches the performance of other models used in similar tasks. Furthermore, during an empirical evaluation with teachers and students, about seven out of ten sentences selected were considered understandable, the rule-based approach slightly outperforming the method incorporating the machine learning model.
Subject headings
- HUMANIORA -- Språk och litteratur -- Studier av enskilda språk (hsv//swe)
- HUMANITIES -- Languages and Literature -- Specific Languages (hsv//eng)
- HUMANIORA -- Språk och litteratur -- Jämförande språkvetenskap och allmän lingvistik (hsv//swe)
- HUMANITIES -- Languages and Literature -- General Language Studies and Linguistics (hsv//eng)
- SAMHÄLLSVETENSKAP -- Utbildningsvetenskap -- Lärande (hsv//swe)
- SOCIAL SCIENCES -- Educational Sciences -- Learning (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Language Technology (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Keyword
- readability
- L2 Swedish
- machine learning
- sentence-level categorization
Publication and Content Type
- ref (subject category)
- kon (subject category)
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