Improving Consistency of Human and Machine Translations
Abstract
Consistency is one of the desired quality features in final translations. For human-only translations (without MT), we rely on the translator’s ability to achieve consistency. For MT, consistency is neither guaranteed nor expected. MT may actually generate inconsistencies, and it is left to the post-editor to introduce consistency in a manual fashion. This work presents a method that facilitates the improvement of consistency without the need of a glossary. It detects inconsistencies in the post-edited work, and gives the post-editor the opportunity to fix the translation towards consistency. We describe the method, which is simple and involves only a short Python script, and also provide numbers that show its positive impact. This method is a contribution to a broader set of quality checks that can improve language quality of human and MT translations.- Anthology ID:
- 2022.amta-upg.8
- Volume:
- Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)
- Month:
- September
- Year:
- 2022
- Address:
- Orlando, USA
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 107–122
- Language:
- URL:
- https://aclanthology.org/2022.amta-upg.8
- DOI:
- Cite (ACL):
- Silvio Picinini. 2022. Improving Consistency of Human and Machine Translations. In Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track), pages 107–122, Orlando, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Improving Consistency of Human and Machine Translations (Picinini, AMTA 2022)