Papers by Vishnu Sharma
Poetry to Prose Conversion in Sanskrit as a Linearisation Task: A Case for Low-Resource Languages (P19-1)
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| Challenge: | Obtaining the proper word ordering, called as the prose ordering, from a verse is often considered a task which requires linguistic expertise. |
| Approach: | They propose a word ordering (linearisation) task that ignores the word arrangement at the verse side. |
| Outcome: | The proposed model outperforms current models in word ordering for the translation task in Sanskrit. |
Building a Word Segmenter for Sanskrit Overnight (L18-1)
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| Challenge: | Sanskrit word segmentation is challenging due to the issue of Sandhi . digitisation efforts have made the manuscripts available in the public domain . |
| Approach: | They propose a deep sequence to sequence model that takes only the sandhied string as input and predicts the unsandhized string. |
| Outcome: | The proposed model improves on the current state of the art by 16.79% . the system can be trained "overnight" and be used for production . |
Learnings from Technological Interventions in a Low Resource Language: A Case-Study on Gondi (2020.lrec-1)
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Devansh Mehta, Sebastin Santy, Ramaravind Kommiya Mothilal, Brij Mohan Lal Srivastava, Alok Sharma, Anurag Shukla, Vishnu Prasad, Venkanna U, Amit Sharma, Kalika Bali
| Challenge: | 40% of all the languages in the world face the danger of extinction in the near future . when a language dies out, future generations lose a vital part of the culture that is necessary to completely understand it. |
| Approach: | They propose to use 4 technology-driven methods of data collection to collect data on Gondi, a low-resource vulnerable language spoken by 2.3 million tribal people in south and central India. |
| Outcome: | The proposed methods collected 12,000 translated words and/or sentences and identified more than 650 community members whose help can be solicited for future translation efforts. |