Legal Text Simplification, Summarization and FAQ Retrieval

Context & Background

The Indian legal system contains a vast array of laws, amendments, and case precedents. However, dense legal jargon and complex language make these documents inaccessible to ordinary citizens. Under-served populations struggle to understand their legal rights, leading to exploitation.

Problems to be Addressed

Legal documents are manually simplified, which is not scalable. Translation tools (like Google Translate) fail to preserve precise legal contexts when converting English statutes into regional Indian languages.

Aims and Objectives

1. Build models for extractive and abstractive legal text summarization.
2. Translate legal texts across 22 scheduled Indian languages.
3. Implement automated FAQ retrieval systems for public legal aid.

Methodology

In collaboration with Nyaaya and Vidhi Legal Center, the project curates Supreme Court documents. NLP transformer architectures (like BART, T5) are customized for legal vocabulary. Models simplify convoluted legal text into 'SARAL' (Simple, Actionable, Recallable, Authoritative) formats.

Expected Outcomes

A public dashboard/website for legal text translation, automatic summarization engines, and interactive legal FAQ assistants.