Siamese Networks for Inference in Malayalam Language Texts

Sara Renjit, Sumam Mary Idicula


Abstract
Natural language inference is a method of finding inferences in language texts. Understanding the meaning of a sentence and its inference is essential in many language processing applications. In this context, we consider the inference problem for a Dravidian language, Malayalam. Siamese networks train the text hypothesis pairs with word embeddings and language agnostic embeddings, and the results are evaluated against classification metrics for binary classification into entailment and contradiction classes. XLM-R embeddings based Siamese architecture using gated recurrent units and bidirectional long short term memory networks provide promising results for this classification problem.
Anthology ID:
2021.ranlp-1.131
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
Month:
September
Year:
2021
Address:
Held Online
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
1167–1173
Language:
URL:
https://aclanthology.org/2021.ranlp-1.131
DOI:
Bibkey:
Cite (ACL):
Sara Renjit and Sumam Mary Idicula. 2021. Siamese Networks for Inference in Malayalam Language Texts. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 1167–1173, Held Online. INCOMA Ltd..
Cite (Informal):
Siamese Networks for Inference in Malayalam Language Texts (Renjit & Idicula, RANLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.ranlp-1.131.pdf
Data
MultiNLISNLI