Automatic Generation of Vocabulary Lists with Multiword Expressions

John S. Y. Lee; Adilet Uvaliyev

doi:10.18653/v1/2023.mwe-1.12

Automatic Generation of Vocabulary Lists with Multiword Expressions

Department of Linguistics and Translation

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

67 Downloads (CityUHK Scholars)

Abstract

The importance of multiword expressions (MWEs) for language learning is well established. While MWE research has been evaluated on various downstream tasks such as syntactic parsing and machine translation, its applications in computer-assisted language learning has been less explored. This paper investigates the selection of MWEs for graded vocabulary lists. Widely used by language teachers and students, these lists recommend a language acquisition sequence to optimize learning efficiency. We automatically generate these lists using difficulty-graded corpora and MWEs extracted based on semantic compositionality. We evaluate these lists on their ability to facilitate text comprehension for learners. Experimental results show that our proposed method generates higher-quality lists than baselines using collocation measures. ©2023 Association for Computational Linguistics

Original language	English
Title of host publication	The 19th Workshop on Multiword Expressions (MWE 2023)
Subtitle of host publication	Proceedings of the Workshop
Publisher	Association for Computational Linguistics
Pages	81–86
ISBN (Electronic)	978-1-959429-59-3
DOIs	https://doi.org/10.18653/v1/2023.mwe-1.12
Publication status	Published - 6 May 2023
Event	19th Workshop on Multiword Expressions (MWE 2023) - Hybrid, Dubrovnik, Croatia Duration: 6 May 2023 → 6 May 2023 https://multiword.org/mwe2023/

Publication series

Name	Workshop on Multiword Expressions, MWE - Proceedings

Conference

Conference	19th Workshop on Multiword Expressions (MWE 2023)
Country/Territory	Croatia
City	Dubrovnik
Period	6/05/23 → 6/05/23
Internet address	https://multiword.org/mwe2023/

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This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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@inproceedings{7270b6b40a8344e7b07aabffa904ed16,

title = "Automatic Generation of Vocabulary Lists with Multiword Expressions",

abstract = "The importance of multiword expressions (MWEs) for language learning is well established. While MWE research has been evaluated on various downstream tasks such as syntactic parsing and machine translation, its applications in computer-assisted language learning has been less explored. This paper investigates the selection of MWEs for graded vocabulary lists. Widely used by language teachers and students, these lists recommend a language acquisition sequence to optimize learning efficiency. We automatically generate these lists using difficulty-graded corpora and MWEs extracted based on semantic compositionality. We evaluate these lists on their ability to facilitate text comprehension for learners. Experimental results show that our proposed method generates higher-quality lists than baselines using collocation measures. {\textcopyright}2023 Association for Computational Linguistics",

author = "Lee, {John S. Y.} and Adilet Uvaliyev",

year = "2023",

month = may,

day = "6",

doi = "10.18653/v1/2023.mwe-1.12",

language = "English",

series = "Workshop on Multiword Expressions, MWE - Proceedings",

publisher = "Association for Computational Linguistics",

pages = "81–86",

booktitle = "The 19th Workshop on Multiword Expressions (MWE 2023)",

address = "United States",

note = "19th Workshop on Multiword Expressions (MWE 2023) ; Conference date: 06-05-2023 Through 06-05-2023",

url = "https://multiword.org/mwe2023/",

}

Lee, JSY & Uvaliyev, A 2023, Automatic Generation of Vocabulary Lists with Multiword Expressions. in The 19th Workshop on Multiword Expressions (MWE 2023): Proceedings of the Workshop. Workshop on Multiword Expressions, MWE - Proceedings, Association for Computational Linguistics, pp. 81–86, 19th Workshop on Multiword Expressions (MWE 2023), Dubrovnik, Croatia, 6/05/23. https://doi.org/10.18653/v1/2023.mwe-1.12

Automatic Generation of Vocabulary Lists with Multiword Expressions. / Lee, John S. Y.; Uvaliyev, Adilet.
The 19th Workshop on Multiword Expressions (MWE 2023): Proceedings of the Workshop. Association for Computational Linguistics, 2023. p. 81–86 (Workshop on Multiword Expressions, MWE - Proceedings).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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N2 - The importance of multiword expressions (MWEs) for language learning is well established. While MWE research has been evaluated on various downstream tasks such as syntactic parsing and machine translation, its applications in computer-assisted language learning has been less explored. This paper investigates the selection of MWEs for graded vocabulary lists. Widely used by language teachers and students, these lists recommend a language acquisition sequence to optimize learning efficiency. We automatically generate these lists using difficulty-graded corpora and MWEs extracted based on semantic compositionality. We evaluate these lists on their ability to facilitate text comprehension for learners. Experimental results show that our proposed method generates higher-quality lists than baselines using collocation measures. ©2023 Association for Computational Linguistics

AB - The importance of multiword expressions (MWEs) for language learning is well established. While MWE research has been evaluated on various downstream tasks such as syntactic parsing and machine translation, its applications in computer-assisted language learning has been less explored. This paper investigates the selection of MWEs for graded vocabulary lists. Widely used by language teachers and students, these lists recommend a language acquisition sequence to optimize learning efficiency. We automatically generate these lists using difficulty-graded corpora and MWEs extracted based on semantic compositionality. We evaluate these lists on their ability to facilitate text comprehension for learners. Experimental results show that our proposed method generates higher-quality lists than baselines using collocation measures. ©2023 Association for Computational Linguistics

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Automatic Generation of Vocabulary Lists with Multiword Expressions

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