Hindi English

Research on Hindi-English language processing focuses on bridging the gap between high-resource English NLP and the needs of the vast Hindi-speaking population. Current efforts concentrate on developing robust benchmarks for tasks like automatic speech recognition (ASR), information retrieval, and machine translation, often employing transformer-based models like BERT and its variants, along with innovative data augmentation techniques to address data scarcity. These advancements are crucial for improving access to technology and information for Hindi speakers, while also providing valuable insights into multilingual NLP and the challenges posed by low-resource languages.