A Review for Large Volumes of Post-edited Data
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:
- 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)