Deploying MT Quality Estimation on a large scale: Lessons learned and open questions

Aleš Tamchyna


Abstract
This talk will focus on Memsource’s experience implementing MT Quality Estimation on a large scale within a translation management system. We will cover the whole development journey: from our early experimentation and the challenges we faced adapting academic models for a real world setting, all the way through to the practical implementation. Since the launch of this feature, we’ve accumulated a significant amount of experience and feedback, which has informed our subsequent development. Lastly we will discuss several open questions regarding the future role of quality estimation in translation.
Anthology ID:
2021.mtsummit-up.21
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:
291–305
Language:
URL:
https://aclanthology.org/2021.mtsummit-up.21
DOI:
Bibkey:
Cite (ACL):
Aleš Tamchyna. 2021. Deploying MT Quality Estimation on a large scale: Lessons learned and open questions. In Proceedings of Machine Translation Summit XVIII: Users and Providers Track, pages 291–305, Virtual. Association for Machine Translation in the Americas.
Cite (Informal):
Deploying MT Quality Estimation on a large scale: Lessons learned and open questions (Tamchyna, MTSummit 2021)
Copy Citation:
Presentation:
 2021.mtsummit-up.21.Presentation.pdf