Bangla Text
Bangla text processing research focuses on developing and applying natural language processing (NLP) techniques to the Bengali language, a low-resource language with significant linguistic complexity. Current research emphasizes building robust models for tasks like sentiment analysis, toxicity detection, and question answering, often leveraging transformer architectures such as BERT and its variants, along with other deep learning approaches. This work is crucial for bridging the digital divide, enabling the development of Bangla-specific applications in various domains, from social media monitoring to healthcare and education, and advancing the broader field of NLP for low-resource languages.
Papers
An Opinion Mining of Text in COVID-19 Issues along with Comparative Study in ML, BERT & RNN
Md. Mahadi Hasan Sany, Mumenunnesa Keya, Sharun Akter Khushbu, Akm Shahariar Azad Rabby, Abu Kaisar Mohammad Masum
An exploratory experiment on Hindi, Bengali hate-speech detection and transfer learning using neural networks
Tung Minh Phung, Jan Cloos