Lexical Normalization for Code-switched Data and its Effect on POS Tagging

Rob van der Goot, Özlem Çetinoğlu


Abstract
Lexical normalization, the translation of non-canonical data to standard language, has shown to improve the performance of many natural language processing tasks on social media. Yet, using multiple languages in one utterance, also called code-switching (CS), is frequently overlooked by these normalization systems, despite its common use in social media. In this paper, we propose three normalization models specifically designed to handle code-switched data which we evaluate for two language pairs: Indonesian-English and Turkish-German. For the latter, we introduce novel normalization layers and their corresponding language ID and POS tags for the dataset, and evaluate the downstream effect of normalization on POS tagging. Results show that our CS-tailored normalization models significantly outperform monolingual ones, and lead to 5.4% relative performance increase for POS tagging as compared to unnormalized input.
Anthology ID:
2021.eacl-main.200
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Month:
April
Year:
2021
Address:
Online
Editors:
Paola Merlo, Jorg Tiedemann, Reut Tsarfaty
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2352–2365
Language:
URL:
https://aclanthology.org/2021.eacl-main.200
DOI:
10.18653/v1/2021.eacl-main.200
Bibkey:
Cite (ACL):
Rob van der Goot and Özlem Çetinoğlu. 2021. Lexical Normalization for Code-switched Data and its Effect on POS Tagging. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 2352–2365, Online. Association for Computational Linguistics.
Cite (Informal):
Lexical Normalization for Code-switched Data and its Effect on POS Tagging (van der Goot & Çetinoğlu, EACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.eacl-main.200.pdf
Code
 ozlemcek/TrDeNormData
Data
Universal Dependencies