Paper Title
A Survey on A Machine Learning based Approach for a Legal Document Simplifier and Reader

Reading Legal documents and understanding them is difficult due to their highly sophisticated language. Thus, many people depend on others for translation and understanding of legal documents and are cheated in the process. There is a pressing need for reliable simplified verbal translation of a legal document. We thus propose an implementation of a Legal Document Simplifier and Reader for the layman. The Legal Document Simplifier and Reader is to help the layman better understand the clauses included in a Legal Document and have the simplified document read out if they are unable to read it. This will eliminate dependence on others for understanding a Legal Document and prevent deception of unassuming unaware civilians. Translating the document from one language to another is also included to make it more convenient for a user. The framework for the proposed implementation includes a camera module to capture an image of the Legal Document, an image processing module to process the image, an OCR(optical character recognition) module for recognizing the text, NLP(Natural Language Processing) module for simplifying difficult terms, Language translation module and TTS(Text-to-Speech) synthesis module to read out the simplified document in the user’s preferred language. Keywords - Legal Document Reader, Machine Translation, NLP, OCR, Text Simplification, Text To Speech