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TweetTaglish: A Dataset for Investigating Tagalog-English Code-Switching

Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)

DOI:10.63317/48h9vaowntod

Abstract

Deploying recent natural language processing innovations to low-resource settings allows for state-of-the-art research findings and applications to be accessed across cultural and linguistic borders. One low-resource setting of increasing interest is code-switching, the phenomenon of combining, swapping, or alternating the use of two or more languages in continuous dialogue. In this paper, we introduce a large dataset (20k+ instances) to facilitate investigation of Tagalog-English code-switching, which has become a popular mode of discourse in Philippine culture. Tagalog is an Austronesian language and former official language of the Philippines spoken by over 23 million people worldwide, but it and Tagalog-English are under-represented in NLP research and practice. We describe our methods for data collection, as well as our labeling procedures. We analyze our resulting dataset, and finally conclude by providing results from a proof-of-concept regression task to establish dataset validity, achieving a strong performance benchmark (R2=0.797-0.909; RMSE=0.068-0.057).

Details

Paper ID
lrec2022-main-225
Pages
pp. 2090-2097
BibKey
herrera-etal-2022-tweettaglish
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
79-10-95546-38-2
Conference
Thirteenth Language Resources and Evaluation Conference
Location
Marseille, France
Date
20 June 2022 25 June 2022

Authors

  • MH

    Megan Herrera

  • AA

    Ankit Aich

  • NP

    Natalie Parde

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