@inproceedings{maxwelll-smith-etal-2022-scoping,
title = "Scoping natural language processing in {I}ndonesian and {M}alay for education applications",
author = "Maxwell-Smith, Zara and
Kohler, Michelle and
Suominen, Hanna",
editor = "Louvan, Samuel and
Madotto, Andrea and
Madureira, Brielen",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.acl-srw.15",
doi = "10.18653/v1/2022.acl-srw.15",
pages = "171--228",
abstract = "Indonesian and Malay are underrepresented in the development of natural language processing (NLP) technologies and available resources are difficult to find. A clear picture of existing work can invigorate and inform how researchers conceptualise worthwhile projects. Using an education sector project to motivate the study, we conducted a wide-ranging overview of Indonesian and Malay human language technologies and corpus work. We charted 657 included studies according to Hirschberg and Manning{'}s 2015 description of NLP, concluding that the field was dominated by exploratory corpus work, machine reading of text gathered from the Internet, and sentiment analysis. In this paper, we identify most published authors and research hubs, and make a number of recommendations to encourage future collaboration and efficiency within NLP in Indonesian and Malay.",
}
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%0 Conference Proceedings
%T Scoping natural language processing in Indonesian and Malay for education applications
%A Maxwell-Smith, Zara
%A Kohler, Michelle
%A Suominen, Hanna
%Y Louvan, Samuel
%Y Madotto, Andrea
%Y Madureira, Brielen
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F maxwelll-smith-etal-2022-scoping
%X Indonesian and Malay are underrepresented in the development of natural language processing (NLP) technologies and available resources are difficult to find. A clear picture of existing work can invigorate and inform how researchers conceptualise worthwhile projects. Using an education sector project to motivate the study, we conducted a wide-ranging overview of Indonesian and Malay human language technologies and corpus work. We charted 657 included studies according to Hirschberg and Manning’s 2015 description of NLP, concluding that the field was dominated by exploratory corpus work, machine reading of text gathered from the Internet, and sentiment analysis. In this paper, we identify most published authors and research hubs, and make a number of recommendations to encourage future collaboration and efficiency within NLP in Indonesian and Malay.
%R 10.18653/v1/2022.acl-srw.15
%U https://aclanthology.org/2022.acl-srw.15
%U https://doi.org/10.18653/v1/2022.acl-srw.15
%P 171-228
Markdown (Informal)
[Scoping natural language processing in Indonesian and Malay for education applications](https://aclanthology.org/2022.acl-srw.15) (Maxwell-Smith et al., ACL 2022)
ACL