Summary of Mahasquad: Bridging Linguistic Divides in Marathi Question-answering, by Ruturaj Ghatage et al.
MahaSQuAD: Bridging Linguistic Divides in Marathi Question-Answering
by Ruturaj Ghatage, Aditya Kulkarni, Rajlaxmi Patil, Sharvi Endait, Raviraj Joshi
First submitted to arxiv on: 20 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
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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 This research aims to improve the accessibility of question-answering systems by developing efficient datasets for low-resource languages. The study focuses on Marathi, an Indic language, and introduces MahaSQuAD, a translated version of the English Question Answering Dataset (SQuAD). The dataset consists of 118,516 training samples, 11,873 validation samples, and 11,803 test samples, along with a gold test set of manually verified examples. To address challenges in maintaining context and handling linguistic nuances, the researchers employed a robust data curation approach. Additionally, they presented a generic method for translating SQuAD into any low-resource language. This scalable approach aims to bridge linguistic and cultural gaps in question-answering systems, making it more accessible to users worldwide. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps make computers better at answering questions in different languages. Right now, most question-answering systems are only good for English speakers. The researchers translated a big dataset called SQuAD from English into Marathi, a language spoken in India. They also created a way to translate other low-resource languages. This makes it easier for people who don’t speak English to use these systems. The researchers hope their work will help bridge the gap between different cultures and languages. |
Keywords
» Artificial intelligence » Question answering
