| dc.contributor.author |
Sharma, Yashvardhan |
|
| dc.date.accessioned |
2024-11-12T09:41:55Z |
|
| dc.date.available |
2024-11-12T09:41:55Z |
|
| dc.date.issued |
2021 |
|
| dc.identifier.uri |
https://ceur-ws.org/Vol-3681/T9-3.pdf |
|
| dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16349 |
|
| dc.description.abstract |
This paper describes the proposed system for the machine translation of Indic language pairs Odia - Hindi and Hindi - Odia for the General Translation and Domain Specific Translation tasks proposed by Forum of Information Retrieval Evaluation(FIRE) in 2023. For general task, the proposed system uses an ensemble of two pre-trained models and for domain specific task, the proposed system uses a pretrained model fine-tuned using domain specific training data filtered from open source datasets |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
CEUR |
en_US |
| dc.subject |
Computer Science |
en_US |
| dc.subject |
Low resource Machine Translation |
en_US |
| dc.subject |
NLLB |
en_US |
| dc.subject |
BART |
en_US |
| dc.subject |
IndicTrans |
en_US |
| dc.subject |
Sentence Similarity |
en_US |
| dc.title |
Fine tuning based Domain Adaptation for Machine Translation of Low Resource Indic Languages |
en_US |
| dc.type |
Article |
en_US |