Bangla Natural Language

Bangla natural language processing (NLP) research focuses on developing computational methods to understand and process the Bangla language, addressing its unique linguistic characteristics and the challenges posed by its low-resource status. Current efforts concentrate on mitigating biases in large language models (LLMs), improving performance on tasks like natural language inference and sentiment analysis using architectures such as BERT and Transformer models, and creating high-quality datasets for various NLP tasks including lemmatization, spell checking, and paraphrase generation. This work is crucial for advancing NLP capabilities in a widely spoken language, enabling applications such as improved machine translation for ethnic media, enhanced social media monitoring, and more accurate text analysis tools.