TY - GEN
T1 - Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathi
AU - Gaikwad, Saurabh Gaikwad
AU - Ranasinghe, Tharindu
AU - Zampieri, Marcos
AU - Homan, Christopher
N1 - This accepted manuscript is distributed under the terms of the Creative Commons Attribution License CC BY [https://creativecommons.org/licenses/by/4.0/], which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
PY - 2021/9
Y1 - 2021/9
N2 - The widespread presence of offensive language on social media motivated the development of systems capable of recognizing such content automatically. Apart from a few notable exceptions, most research on automatic offensive language identification has dealt with English. To address this shortcoming, we introduce MOLD, the Marathi Offensive Language Dataset. MOLD is the first dataset of its kind compiled for Marathi, thus opening a new domain for research in low-resource Indo-Aryan languages. We present results from several machine learning experiments on this dataset, including zero-short and other transfer learning experiments on state-of-the-art cross-lingual transformers from existing data in Bengali, English, and Hindi.
AB - The widespread presence of offensive language on social media motivated the development of systems capable of recognizing such content automatically. Apart from a few notable exceptions, most research on automatic offensive language identification has dealt with English. To address this shortcoming, we introduce MOLD, the Marathi Offensive Language Dataset. MOLD is the first dataset of its kind compiled for Marathi, thus opening a new domain for research in low-resource Indo-Aryan languages. We present results from several machine learning experiments on this dataset, including zero-short and other transfer learning experiments on state-of-the-art cross-lingual transformers from existing data in Bengali, English, and Hindi.
UR - https://arxiv.org/abs/2109.03552
U2 - 10.48550/arXiv.2109.03552
DO - 10.48550/arXiv.2109.03552
M3 - Conference publication
BT - Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
ER -