Indian Language

Research on Indian languages focuses on developing and evaluating natural language processing (NLP) models for the diverse linguistic landscape of India, addressing the challenges posed by low-resource languages and significant dialectal variation. Current efforts concentrate on adapting and fine-tuning multilingual transformer models, such as BERT and its variants, for tasks like machine translation, question answering, and sentiment analysis, alongside developing new benchmarks and datasets to facilitate robust evaluation. This work is crucial for bridging the digital divide, enabling wider access to technology and information in India, and advancing the broader field of multilingual NLP.