NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfer
Hwijeen Ahn, Jimin Sun, Chan Young Park, Jungyun Seo · 2020
This paper describes our approach to the task of identifying offensive languages in a multilingual setting.We investigate two data augmentation strategies: using additional semi-supervised labels with different thresholds and cross-lingual transfer with data selection.Leveraging the semisupervised dataset resulted in performance improvements compared to the baseline trained solely with the manually-annotated dataset.We propose a new metric, Translation Embedding Distance, to measure the transferability of instances for cross-lingual data selection.We also introduce various preprocessing steps tailored for social media text along with methods to fine-tune the pre-trained multilingual BERT (mBERT) for offensive language identification.Our multilingual systems achieved competitive results in Greek, Danish, and Turkish at OffensEval 2020.