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In the digital age, maintaining respectful and safe online communication is paramount. This research addresses the problem of identifying and categorizing hate speech in both English and English-Punjabi sentences. Adopting Natural Language Processing (NLP) techniques, this research work employs advanced deep learning models to accurately detect various levels of hate speech severity. By combining cross-lingual expertise and a fine-tuned multiclass classification approach, the research aims to provide a robust solution for real-time hate speech detection with 91% accuracy, contributing to creating inclusive and secure online environments.

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P-HSSN: A Framework to Detect Punjabi Hate Speech in Social Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Ravneet Kaur,
  • Sukhvir Singh,
  • Sartaj Singh,
  • Prabhinderpal Singh,
  • Jasraj Singh

摘要

In the digital age, maintaining respectful and safe online communication is paramount. This research addresses the problem of identifying and categorizing hate speech in both English and English-Punjabi sentences. Adopting Natural Language Processing (NLP) techniques, this research work employs advanced deep learning models to accurately detect various levels of hate speech severity. By combining cross-lingual expertise and a fine-tuned multiclass classification approach, the research aims to provide a robust solution for real-time hate speech detection with 91% accuracy, contributing to creating inclusive and secure online environments.