Zero-shot Cross-lingual Content Filtering: Offensive Language and Hate Speech Detection
Andraž Pelicon, Ravi Shekhar, Matej Martinc, Blaž Škrlj, Matthew Purver, Senja Pollak · Queen Mary Research Online (Queen Mary University of London) · 2021
We present a system for zero-shot crosslingual offensive language and hate speech classification.The system was trained on English datasets and tested on a task of detecting hate speech and offensive social media content in a number of languages without any additional training.Experiments show an impressive ability of both models to generalize from English to other languages.There is however an expected gap in performance between the tested cross-lingual models and the monolingual models.The best performing model (offensive content classifier) is available online as a REST API.