katildakat at SemEval-2021 Task 1: Lexical Complexity Prediction of Single Words and Multi-Word Expressions in English

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorVoskoboinik, Ekaterinaen_US
dc.contributor.departmentSpeech Recognitionen_US
dc.contributor.editorPalmer, Alexisen_US
dc.contributor.editorSchneider, Nathanen_US
dc.contributor.editorSchluter, Natalieen_US
dc.contributor.editorEmerson, Guyen_US
dc.contributor.editorHerbelot, Aurelieen_US
dc.contributor.editorZhu, Xiaodanen_US
dc.date.accessioned2023-02-01T09:11:30Z
dc.date.available2023-02-01T09:11:30Z
dc.date.issued2021en_US
dc.descriptionFunding Information: I would like to express my gratitude to the anonymous reviewer for their insightful and helpful comments. I also want thank Ragheb Al-Ghezi for proofreading and Mikko Kurimo for his comments on an earlier draft of the paper. Lastly, I want to say thank you to Science-IT team for providing computational environment used in the experiments. This work is a part of DigiTala project which is funded by the Academy of Finland (grant number 322625). Publisher Copyright: © 2021 Association for Computational Linguistics.
dc.description.abstractThis paper describes systems submitted to SemEval 2021 Task 1: Lexical Complexity Prediction (LCP). We compare a linear and a nonlinear regression models trained to work for both tracks of the task. We show that both systems are able to generalize better when supplied with information about complexities of single word and multi-word expression (MWE) targets simultaneously. This approach proved to be the most beneficial for multi-word expression targets. We also demonstrate that some hand-crafted features differ in their importance for the target types.en
dc.description.versionPeer revieweden
dc.format.extent6
dc.format.extent700-705
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationVoskoboinik , E 2021 , katildakat at SemEval-2021 Task 1: Lexical Complexity Prediction of Single Words and Multi-Word Expressions in English . in A Palmer , N Schneider , N Schluter , G Emerson , A Herbelot & X Zhu (eds) , SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop . SemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshop , Association for Computational Linguistics , pp. 700-705 , International Workshop on Semantic Evaluation , Bangkok , Thailand , 05/08/2021 . https://doi.org/10.18653/v1/2021.semeval-1.91en
dc.identifier.doi10.18653/v1/2021.semeval-1.91en_US
dc.identifier.isbn9781954085701
dc.identifier.otherPURE UUID: 7c01abab-219f-41e5-9bfd-07b8cef4049ben_US
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dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/119547
dc.identifier.urnURN:NBN:fi:aalto-202302011897
dc.language.isoenen
dc.relation.ispartofInternational Workshop on Semantic Evaluationen
dc.relation.ispartofseriesSemEval 2021 - 15th International Workshop on Semantic Evaluation, Proceedings of the Workshopen
dc.rightsopenAccessen
dc.titlekatildakat at SemEval-2021 Task 1: Lexical Complexity Prediction of Single Words and Multi-Word Expressions in Englishen
dc.typeConference article in proceedingsfi
dc.type.versionpublishedVersion
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