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2022 ACL ACL 2022

UMUTeam@LT-EDI-ACL2022: Detecting homophobic and transphobic comments in Tamil

Abstract

AbstractThis working-notes are about the participation of the UMUTeam in a LT-EDI shared task concerning the identification of homophobic and transphobic comments in YouTube. These comments are written in English, which has high availability to machine-learning resources; Tamil, which has fewer resources; and a transliteration from Tamil to Roman script combined with English sentences. To carry out this shared task, we train a neural network that combines several feature sets applying a knowledge integration strategy. These features are linguistic features extracted from a tool developed by our research group and contextual and non-contextual sentence embeddings. We ranked 7th for English subtask (macro f1-score of 45%), 3rd for Tamil subtask (macro f1-score of 82%), and 2nd for Tamil-English subtask (macro f1-score of 58%).

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — tamil nlp
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

José García-Díaz , Camilo Caparros-Laiz , Rafael Valencia-García

Topics

Deep Learning > Architectures > Neural Networks Natural Language Processing > Applications > Text Classification Machine Learning > Core Methods > Feature Extraction

Keywords

feature extraction multilingual nlp sentence embedding linguistic feature hate speech detection tamil language neural network tamil nlp
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