Preserving high MT quality for content with inline tags

Konstantin Savenkov, Grigory Sapunov, Pavel Stepachev


Abstract
Attendees will learn about how we use machine translation to provide targeted, high MT quality for content with inline tags. We offer a new and innovative approach to inserting tags into the translated text in a way that reliably preserves their quality. This process can achieve better MT quality and lower costs, as it is MT-independent, and can be used for all languages, MT engines, and use cases.
Anthology ID:
2021.mtsummit-up.19
Volume:
Proceedings of Machine Translation Summit XVIII: Users and Providers Track
Month:
August
Year:
2021
Address:
Virtual
Editors:
Janice Campbell, Ben Huyck, Stephen Larocca, Jay Marciano, Konstantin Savenkov, Alex Yanishevsky
Venue:
MTSummit
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
246–276
Language:
URL:
https://aclanthology.org/2021.mtsummit-up.19
DOI:
Bibkey:
Cite (ACL):
Konstantin Savenkov, Grigory Sapunov, and Pavel Stepachev. 2021. Preserving high MT quality for content with inline tags. In Proceedings of Machine Translation Summit XVIII: Users and Providers Track, pages 246–276, Virtual. Association for Machine Translation in the Americas.
Cite (Informal):
Preserving high MT quality for content with inline tags (Savenkov et al., MTSummit 2021)
Copy Citation:
Presentation:
 2021.mtsummit-up.19.Presentation.pdf