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arXiv · 2505.11177

Low-Resource Language Processing: An OCR-Driven Summarization and Translation Pipeline

Hrishit Madhavi·Jacob Cherian·Yuvraj Khamkar·Dhananjay Bhagat
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Abstract

This paper presents an end-to-end suite for multilingual information extraction and processing from image-based documents. The system uses Optical Character Recognition (Tesseract) to extract text in languages such as English, Hindi, and Tamil, and then a pipeline involving large language model APIs (Gemini) for cross-lingual translation, abstractive summarization, and re-translation into a target language. Additional modules add sentiment analysis (TensorFlow), topic classification (Transformers), and date extraction (Regex) for better document comprehension. Made available in an accessible Gradio interface, the current research shows a real-world application of libraries, models, and APIs to close the language gap and enhance access to information in image media across different linguistic environments

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Hrishit Madhavi, Jacob Cherian, Yuvraj Khamkar, Dhananjay Bhagat. 2025-05-16. Low-Resource Language Processing: An OCR-Driven Summarization and Translation Pipeline. https://arxiv.org/abs/2505.11177

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