QuickEdit: Editing Text & Translations by Crossing Words Out

David Grangier, Michael Auli


Abstract
We propose a framework for computer-assisted text editing. It applies to translation post-editing and to paraphrasing. Our proposal relies on very simple interactions: a human editor modifies a sentence by marking tokens they would like the system to change. Our model then generates a new sentence which reformulates the initial sentence by avoiding marked words. The approach builds upon neural sequence-to-sequence modeling and introduces a neural network which takes as input a sentence along with change markers. Our model is trained on translation bitext by simulating post-edits. We demonstrate the advantage of our approach for translation post-editing through simulated post-edits. We also evaluate our model for paraphrasing through a user study.
Anthology ID:
N18-1025
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marilyn Walker, Heng Ji, Amanda Stent
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
272–282
Language:
URL:
https://aclanthology.org/N18-1025
DOI:
10.18653/v1/N18-1025
Bibkey:
Cite (ACL):
David Grangier and Michael Auli. 2018. QuickEdit: Editing Text & Translations by Crossing Words Out. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 272–282, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
QuickEdit: Editing Text & Translations by Crossing Words Out (Grangier & Auli, NAACL 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-1/N18-1025.pdf
Data
WMT 2014