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
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
BanglaNLP at BLP-2023 Task 2: Benchmarking different Transformer Models for Sentiment Analysis of Bangla Social Media Posts
Saumajit Saha, Albert Nanda
BaitBuster-Bangla: A Comprehensive Dataset for Clickbait Detection in Bangla with Multi-Feature and Multi-Modal Analysis
Abdullah Al Imran, Md Sakib Hossain Shovon, M. F. Mridha
Feature Extraction Using Deep Generative Models for Bangla Text Classification on a New Comprehensive Dataset
Md. Rafi-Ur-Rashid, Sami Azam, Mirjam Jonkman
Performance Enhancement Leveraging Mask-RCNN on Bengali Document Layout Analysis
Shrestha Datta, Md Adith Mollah, Raisa Fairooz, Tariful Islam Fahim