Crosslingual Content Scoring in Five Languages Using Machine-Translation and Multilingual Transformer Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AHPF75PD8" target="_blank" >RIV/00216208:11320/23:HPF75PD8 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/10.1007/s40593-023-00370-1" target="_blank" >https://link.springer.com/10.1007/s40593-023-00370-1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s40593-023-00370-1" target="_blank" >10.1007/s40593-023-00370-1</a>
Alternative languages
Result language
angličtina
Original language name
Crosslingual Content Scoring in Five Languages Using Machine-Translation and Multilingual Transformer Models
Original language description
"Abstractn This paper investigates crosslingual content scoring, a scenario where scoring models trained on learner data in one language are applied to data in a different language. We analyze data in five different languages (Chinese, English, French, German and Spanish) collected for three prompts of the established English ASAP content scoring dataset. We cross the language barrier by means of both shallow and deep learning crosslingual classification models using both machine translation and multilingual transformer models. We find that a combination of machine translation and multilingual models outperforms each method individually - our best results are reached when combining the available data in different languages, i.e. first training a model on the large English ASAP dataset before fine-tuning on smaller amounts of training data in the target language."
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"International Journal of Artificial Intelligence in Education"
ISSN
1560-4292
e-ISSN
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Volume of the periodical
""
Issue of the periodical within the volume
2023-6-19
Country of publishing house
US - UNITED STATES
Number of pages
27
Pages from-to
1-27
UT code for WoS article
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EID of the result in the Scopus database
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