Projects per year
Abstract
Modern sentence-level NMT systems often produce plausible translations of isolated sentences. However, when put in context, these translations may end up being inconsistent with each other. We propose a monolingual DocRepair model to correct inconsistencies between sentence-level translations. DocRepair performs automatic post-editing on a sequence of sentence-level translations, refining translations of sentences in context of each other. For training, the DocRepair model requires only monolingual document-level data in the target language. It is trained as a monolingual sequence-to-sequence model that maps inconsistent groups of sentences into consistent ones. The consistent groups come from the original training data; the inconsistent groups are obtained by sampling round-trip translations for each isolated sentence. We show that this approach successfully imitates inconsistencies we aim to fix: using contrastive evaluation, we show large improvements in the translation of several contextual phenomena in an English!Russian translation task, as well as improvements in the BLEU score. We also conduct a human evaluation and show a strong preference of the annotators to corrected translations over the baseline ones. Moreover, we analyze which discourse phenomena are hard to capture using monolingual data only.
Original language | English |
---|---|
Title of host publication | Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing |
Place of Publication | Hong Kong, China |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 876-885 |
Number of pages | 10 |
ISBN (Print) | 978-1-950737-90-1 |
DOIs | |
Publication status | Published - 3 Nov 2019 |
Event | 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing - Hong Kong, Hong Kong Duration: 3 Nov 2019 → 7 Nov 2019 https://www.emnlp-ijcnlp2019.org/ |
Conference
Conference | 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing |
---|---|
Abbreviated title | EMNLP-IJCNLP 2019 |
Country/Territory | Hong Kong |
City | Hong Kong |
Period | 3/11/19 → 7/11/19 |
Internet address |
Fingerprint
Dive into the research topics of 'Context-Aware Monolingual Repair for Neural Machine Translation'. Together they form a unique fingerprint.Projects
- 2 Finished