Papers by Jerin Philip
Monolingual Adapters for Zero-Shot Neural Machine Translation (2020.emnlp-main)
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| Challenge: | Existing adapter layers are more parameter-efficient and provide better performance than bilingual ones. |
| Approach: | They propose to use monolingual adapter layers instead of bilingual ones to compose them and generalize to unseen language pairs. |
| Outcome: | The proposed adapter layer formalism achieves a median improvement of +2.77 BLEU points over a 20-language multilingual Transformer baseline trained on TED talks. |
A Multilingual Parallel Corpora Collection Effort for Indian Languages (2020.lrec-1)
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| Challenge: | Currently, neural network based approaches for machine translation are data hungry and sentence-level aligned parallel pairs are the currency. |
| Approach: | They propose to build sentence aligned parallel corpora across 10 Indian languages using online sources which have content shared across languages. |
| Outcome: | The proposed corpora significantly extends existing resources that are either not large enough or are restricted to a specific domain (such as health). |
CVIT’s submissions to WAT-2019 (D19-52)
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| Challenge: | In this paper, we explore multiway-models for Indian languages. |
| Approach: | They propose to use a Transformer architecture to experiment with multilingual models and methods for low-resource languages. |
| Outcome: | The proposed system is feasible in low-resource languages. |