A Review for Large Volumes of Post-edited Data

Silvio Picinini


Abstract
Interested in being more confident about the quality of your post-edited data? This is a session to learn how to create a Longitudinal Review that looks at specific aspects of quality in a systematic way, for the entire content and not just for a sample. Are you a project manager for a multilingual project? The Longitudinal Review can give insights to help project management, even if you are not a speaker of the target language. And it can help you detect issues that a Sample Review may not detect. Please come learn more about this new way to look at review.
Anthology ID:
2021.mtsummit-up.10
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:
98–130
Language:
URL:
https://aclanthology.org/2021.mtsummit-up.10
DOI:
Bibkey:
Cite (ACL):
Silvio Picinini. 2021. A Review for Large Volumes of Post-edited Data. In Proceedings of Machine Translation Summit XVIII: Users and Providers Track, pages 98–130, Virtual. Association for Machine Translation in the Americas.
Cite (Informal):
A Review for Large Volumes of Post-edited Data (Picinini, MTSummit 2021)
Copy Citation:
Presentation:
 2021.mtsummit-up.10.Presentation.pdf