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
Static and Dynamic Synthesis of Bengali and Devanagari Signatures
Miguel A. Ferrer, Sukalpa Chanda, Moises Diaz, Chayan Kr. Banerjee, Anirban Majumdar, Cristina Carmona-Duarte, Parikshit Acharya, Umapada Pal
Detecting Racist Text in Bengali: An Ensemble Deep Learning Framework
S. S. Saruar, Nusrat, Sadia
nlpBDpatriots at BLP-2023 Task 2: A Transfer Learning Approach to Bangla Sentiment Analysis
Dhiman Goswami, Md Nishat Raihan, Sadiya Sayara Chowdhury Puspo, Marcos Zampieri
nlpBDpatriots at BLP-2023 Task 1: A Two-Step Classification for Violence Inciting Text Detection in Bangla
Md Nishat Raihan, Dhiman Goswami, Sadiya Sayara Chowdhury Puspo, Marcos Zampieri