Summary of Survey Of Pseudonymization, Abstractive Summarization & Spell Checker For Hindi and Marathi, by Rasika Ransing et al.
Survey of Pseudonymization, Abstractive Summarization & Spell Checker for Hindi and Marathi
by Rasika Ransing, Mohammed Amaan Dhamaskar, Ayush Rajpurohit, Amey Dhoke, Sanket Dalvi
First submitted to arxiv on: 24 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a platform for Natural Language Processing (NLP) that enables users to utilize features like text anonymization, abstractive text summarization, and spell checking in English, Hindi, and Marathi. This platform aims to serve enterprise and consumer clients who predominantly use Indian Regional Languages. The research focuses on the underserved regional languages of India, such as Marathi and Hindi, which remain a significant challenge despite progress in NLP applications for widely spoken languages. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a special tool that helps people understand and work with Indian languages like Marathi and Hindi better. It’s important because many Indians use these languages to communicate and do business, but there haven’t been enough computer programs to help them. The researchers are trying to change this by building a platform that can help with tasks like hiding personal information from text, making summaries of long texts, and checking spelling. |
Keywords
» Artificial intelligence » Natural language processing » Nlp » Summarization
