Improving Rare Word Translation With Dictionaries and Attention Masking

Fuente: arXiv
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Autores principales: Sible, Kenneth J., Chiang, David
Formato: Preprint
Publicado: 2024
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author Sible, Kenneth J.
Chiang, David
author_facet Sible, Kenneth J.
Chiang, David
contents In machine translation, rare words continue to be a problem for the dominant encoder-decoder architecture, especially in low-resource and out-of-domain translation settings. Human translators solve this problem with monolingual or bilingual dictionaries. In this paper, we propose appending definitions from a bilingual dictionary to source sentences and using attention masking to link together rare words with their definitions. We find that including definitions for rare words improves performance by up to 1.0 BLEU and 1.6 MacroF1.
format Preprint
id arxiv_https___arxiv_org_abs_2408_09075
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Improving Rare Word Translation With Dictionaries and Attention Masking
Sible, Kenneth J.
Chiang, David
Computation and Language
Machine Learning
In machine translation, rare words continue to be a problem for the dominant encoder-decoder architecture, especially in low-resource and out-of-domain translation settings. Human translators solve this problem with monolingual or bilingual dictionaries. In this paper, we propose appending definitions from a bilingual dictionary to source sentences and using attention masking to link together rare words with their definitions. We find that including definitions for rare words improves performance by up to 1.0 BLEU and 1.6 MacroF1.
title Improving Rare Word Translation With Dictionaries and Attention Masking
topic Computation and Language
Machine Learning
url https://arxiv.org/abs/2408.09075