Natural Language Processing Model for Hindi to Tulu Translation

Language specificity comes alive through its unique idiomatic expressions, cultural references, and syntactic structures, which often resist straightforward translation. Capturing these subtleties requires careful adaptation to preserve both the meaning of the source text and its cultural essence. This delicate interplay between linguistic precision and cultural sensitivity is at the heart of effective translation. This research explores the challenges and implications of translating Hindi, one of India’s most widely spoken languages, into Tulu, a Dravidian language primarily spoken along the coastal regions of Kerala and Karnataka. Given the distinct linguistic and cultural features of Hindi and Tulu, translating Hindi’s diverse expressions and complex syntax into Tulu poses unique challenges. To bridge this gap, various translation strategies have been employed to retain Hindi’s colloquial expressions, cultural nuances, and emotional depth while ensuring clarity and relatability for a Tulu-speaking audience. This study sheds light on the intricate balancing act between linguistic accuracy and cultural adaptation. Through a detailed analysis of translated texts and interviews with translators, the research offers meaningful insights into the art and science of cross-linguistic translation. These findings underscore the importance of preserving regional languages and fostering better cultural understanding through thoughtful and effective translation practices.