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

Hrishit Madhavi, Jacob Cherian, Yuvraj Khamkar, Dhananjay Bhagat
5/16/2025
cs.CLcs.AI

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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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Cite this paper

@article{madhavi2025lowresource,
  title  = {Low-Resource Language Processing: An OCR-Driven Summarization and Translation Pipeline},
  author = {Hrishit Madhavi and Jacob Cherian and Yuvraj Khamkar and Dhananjay Bhagat},
  year   = {2025},
  eprint = {2505.11177},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2505.11177v1}
}

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