Bicleaner at WMT 2020: Universitat d'Alacant-Prompsit's submission to the parallel corpus filtering shared task

Esplà-Gomis, Miquel; Sánchez-Cartagena, Víctor M.; Zaragoza-Bernabeu, Jaume; Sánchez-Martínez, Felipe

doi:10.5281/zenodo.6580098

2020

DOI: 10.5281/zenodo.6580098

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Bicleaner at WMT 2020: Universitat d'Alacant-Prompsit's submission to the parallel corpus filtering shared task

Miquel Esplà-Gomis

Víctor M. Sánchez-Cartagena

Jaume Zaragoza-Bernabeu³

et al.

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2021

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Cited by 1 publication

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Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation

Briakou¹,

Carpuat²

2021

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Confer

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While it has been shown that Neural Machine Translation (NMT) is highly sensitive to noisy parallel training samples, prior work treats all types of mismatches between source and target as noise. As a result, it remains unclear how samples that are mostly equivalent but contain a small number of semantically divergent tokens impact NMT training. To close this gap, we analyze the impact of different types of fine-grained semantic divergences on Transformer models. We show that models trained on synthetic divergences output degenerated text more frequently and are less confident in their predictions. Based on these findings, we introduce a divergent-aware NMT framework that uses factors to help NMT recover from the degradation caused by naturally occurring divergences, improving both translation quality and model calibration on EN↔FR tasks.

show abstract

Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation

Briakou¹,

Carpuat²

2021

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Confer

View full text Add to dashboard Cite

show abstract

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Bicleaner at WMT 2020: Universitat d'Alacant-Prompsit's submission to the parallel corpus filtering shared task

Cited by 1 publication

References 16 publications

Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation

Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation

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