Halegannada to English Translation using Machine Learning

Halegannada, the ancient Kannada language, poses key linguistic challenges due to its intricate structure and scarce digital resources. The suggested system facilitates hassle free translation of Halegannada to English through the union of static lexical mapping with intelligent API-based processing. A hybrid pipeline is implemented using a special Halegannada Hosagannada dictionary combined with pre-trained external APIs for improved accuracy. Tokenization, word-level mapping, and sentence reconstruction are employed by the algorithm to preserve grammatical and contextual correctness. Transfer based mapping and semantic reordering address the absence of large parallel corpora. Error handling processes control OCR noise, dictionary misses, and image irregularities. Google Gemini OCR reads text off of historical documents, with the DeepSeek Translation API translating to English. Dictionary lookup, image preprocessing using Pillow, and API interaction are controlled by a modular Python backend through workflows. This complete framework demonstrates an effective, scalable approach for translating low-resource languages and assists in preserving Halegannada literature in a digital format.