Improving Rare Word Translation With Dictionaries and Attention Masking
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866929483168088064 |
|---|---|
| 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 |