Neural Automatic Post-Editing Using Prior Alignment and Reranking

Santanu Pal, Sudip Kumar Naskar, Mihaela Vela, Qun Liu, Josef van Genabith


Abstract
We present a second-stage machine translation (MT) system based on a neural machine translation (NMT) approach to automatic post-editing (APE) that improves the translation quality provided by a first-stage MT system. Our APE system (APE_Sym) is an extended version of an attention based NMT model with bilingual symmetry employing bidirectional models, mt–pe and pe–mt. APE translations produced by our system show statistically significant improvements over the first-stage MT, phrase-based APE and the best reported score on the WMT 2016 APE dataset by a previous neural APE system. Re-ranking (APE_Rerank) of the n-best translations from the phrase-based APE and APE_Sym systems provides further substantial improvements over the symmetric neural APE model. Human evaluation confirms that the APE_Rerank generated PE translations improve on the previous best neural APE system at WMT 2016.
Anthology ID:
E17-2056
Volume:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
Month:
April
Year:
2017
Address:
Valencia, Spain
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
349–355
Language:
URL:
https://aclanthology.org/E17-2056
DOI:
Bibkey:
Cite (ACL):
Santanu Pal, Sudip Kumar Naskar, Mihaela Vela, Qun Liu, and Josef van Genabith. 2017. Neural Automatic Post-Editing Using Prior Alignment and Reranking. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 349–355, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Neural Automatic Post-Editing Using Prior Alignment and Reranking (Pal et al., EACL 2017)
Copy Citation:
PDF:
https://preview.aclanthology.org/paclic-22-ingestion/E17-2056.pdf
Data
WMT 2016