Summary of Bhashaverse : Translation Ecosystem For Indian Subcontinent Languages, by Vandan Mujadia et al.
BhashaVerse : Translation Ecosystem for Indian Subcontinent Languages
by Vandan Mujadia, Dipti Misra Sharma
First submitted to arxiv on: 5 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 proposes a novel approach to developing translation models for 36 Indian languages, leveraging parallel corpora and other types of datasets. The task is challenging due to script variations, phonetic differences, and syntactic diversity across languages. To address these issues, the researchers create synthetic data augmentation techniques for low-resource languages like Khasi and Santali, while also normalizing script variations in languages such as Kashmiri and Sindhi. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper develops translation models for 36 Indian languages, including many that are not well-represented in current language datasets. To do this, the researchers create special kinds of datasets called parallel corpora for all 36 languages. They also come up with ways to deal with challenges like different scripts and writing systems used in some languages. |
Keywords
» Artificial intelligence » Synthetic data » Translation
