cantnlp@LT-EDI-2024: Automatic Detection of Anti-LGBTQ+ Hate Speech in
  Under-resourced Languages
Sidney G. -J. Wong Matthew Durward
This paper describes our homophobia/transphobia in social media comments
detection system developed as part of the shared task at LT-EDI-2024. We took a
transformer-based approach to develop our multiclass classification model for
ten language conditions (English, Spanish, Gujarati, Hindi, Kannada, Malayalam,
Marathi, Tamil, Tulu, and Telugu). We introduced synthetic and organic
instances of script-switched language data during domain adaptation to mirror
the linguistic realities of social media language as seen in the labelled
training data. Our system ranked second for Gujarati and Telugu with varying
levels of performance for other language conditions. The results suggest
incorporating elements of paralinguistic behaviour such as script-switching may
improve the performance of language detection systems especially in the cases
of under-resourced languages conditions.