Ona de Gibert Bonet


2021

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Transfer Learning with Shallow Decoders: BSC at WMT2021’s Multilingual Low-Resource Translation for Indo-European Languages Shared Task
Ksenia Kharitonova | Ona de Gibert Bonet | Jordi Armengol-Estapé | Mar Rodriguez i Alvarez | Maite Melero
Proceedings of the Sixth Conference on Machine Translation

This paper describes the participation of the BSC team in the WMT2021’s Multilingual Low-Resource Translation for Indo-European Languages Shared Task. The system aims to solve the Subtask 2: Wikipedia cultural heritage articles, which involves translation in four Romance languages: Catalan, Italian, Occitan and Romanian. The submitted system is a multilingual semi-supervised machine translation model. It is based on a pre-trained language model, namely XLM-RoBERTa, that is later fine-tuned with parallel data obtained mostly from OPUS. Unlike other works, we only use XLM to initialize the encoder and randomly initialize a shallow decoder. The reported results are robust and perform well for all tested languages.

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Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan
Jordi Armengol-Estapé | Casimiro Pio Carrino | Carlos Rodriguez-Penagos | Ona de Gibert Bonet | Carme Armentano-Oller | Aitor Gonzalez-Agirre | Maite Melero | Marta Villegas
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021