Breaking Language Barriers: A Question Answering Dataset for Hindi and Marathi

arXiv:2308.09862v3 Announce Type: replace
Abstract: The recent advances in deep-learning have led to the development of highly sophisticated systems with an unquenchable appetite for data. On the other hand, building good deep-learning models for low-resource languages remains a challenging task. This paper focuses on developing a Question Answering dataset for two such languages- Hindi and Marathi. Despite Hindi being the 3rd most spoken language worldwide, with 345 million speakers, and Marathi being the 11th most spoken language globally, with 83.2 …

abstract advances arxiv breaking building cs.cl data dataset development good hindi language languages low paper question question answering systems type