DeepAI
Log In Sign Up

Diving Deep into Context-Aware Neural Machine Translation

10/19/2020
by   Jingjing Huo, et al.
0

Context-aware neural machine translation (NMT) is a promising direction to improve the translation quality by making use of the additional context, e.g., document-level translation, or having meta-information. Although there exist various architectures and analyses, the effectiveness of different context-aware NMT models is not well explored yet. This paper analyzes the performance of document-level NMT models on four diverse domains with a varied amount of parallel document-level bilingual data. We conduct a comprehensive set of experiments to investigate the impact of document-level NMT. We find that there is no single best approach to document-level NMT, but rather that different architectures come out on top on different tasks. Looking at task-specific problems, such as pronoun resolution or headline translation, we find improvements in the context-aware systems, even in cases where the corpus-level metrics like BLEU show no significant improvement. We also show that document-level back-translation significantly helps to compensate for the lack of document-level bi-texts.

READ FULL TEXT

page 5

page 6

page 7

page 8

page 9

page 11

page 12

page 14

09/13/2021

Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information

Context-aware neural machine translation (NMT) incorporates contextual i...
03/12/2019

Context-Aware Learning for Neural Machine Translation

Interest in larger-context neural machine translation, including documen...
12/28/2020

Towards Fully Automated Manga Translation

We tackle the problem of machine translation of manga, Japanese comics. ...
10/19/2022

A baseline revisited: Pushing the limits of multi-segment models for context-aware translation

This paper addresses the task of contextual translation using multi-segm...
03/31/2021

Divide and Rule: Training Context-Aware Multi-Encoder Translation Models with Little Resources

Multi-encoder models are a broad family of context-aware Neural Machine ...
09/19/2020

Long-Short Term Masking Transformer: A Simple but Effective Baseline for Document-level Neural Machine Translation

Many document-level neural machine translation (NMT) systems have explor...