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

• URL: http://arxiv.org/abs/2505.11177v1
• Date: Fri, 16 May 2025 12:20:37 GMT
• Title: Low-Resource Language Processing: An OCR-Driven Summarization and Translation Pipeline
• Authors: Hrishit Madhavi, Jacob Cherian, Yuvraj Khamkar, Dhananjay Bhagat,
• Abstract summary: This paper presents an end-to-end suite for multilingual information extraction and processing from image-based documents.<n>The system uses Optical Character Recognition (Tesseract) to extract text in languages such as English, Hindi, and Tamil.<n>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.
• Score: 0.0
• License: http://creativecommons.org/publicdomain/zero/1.0/
• 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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