Multilingual Hate Speech Detection and Target Identification in Devanagari-Scripted Languages
Accepted at Chipsal @ COLING 2025. This study addresses hate speech detection and target identification in Devanagari-scripted languages (Hindi, Marathi, Nepali, Bhojpuri, Sanskrit). Subtask B focuses on detecting hate speech, while Subtask C identifies specific targets, such as individuals or communities. The proposed MultilingualRobertaClass model, based on the ia-multilingual-transliterated-roberta transformer, uses contextualized embeddings for multilingual and transliterated contexts. It achieved 88.40% accuracy in Subtask B and 66.11% in Subtask C on the test set.