Brand Consistency for Multilingual E-commerce Machine Translation

Bryan Zhang, Stephan Walter, Saurabh Chetan Birari, Ozlem Eren


Abstract
In the realm of e-commerce, it is crucial to ensure consistent localization of brand terms in product information translations. With the ever-evolving e-commerce landscape, new brands and their localized versions are consistently emerging. However, these diverse brand forms and aliases present a significant challenge in machine translation (MT). This study investigates MT brand consistency problem in multilingual e-commerce and proposes practical and sustainable solutions to maintain brand consistency in various scenarios within the e-commerce industry. Through experimentation and analysis of an English-Arabic MT system, we demonstrate the effectiveness of our proposed solutions.
Anthology ID:
2023.mtsummit-users.17
Volume:
Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track
Month:
September
Year:
2023
Address:
Macau SAR, China
Editors:
Masaru Yamada, Felix do Carmo
Venue:
MTSummit
SIG:
Publisher:
Asia-Pacific Association for Machine Translation
Note:
Pages:
173–182
Language:
URL:
https://aclanthology.org/2023.mtsummit-users.17
DOI:
Bibkey:
Cite (ACL):
Bryan Zhang, Stephan Walter, Saurabh Chetan Birari, and Ozlem Eren. 2023. Brand Consistency for Multilingual E-commerce Machine Translation. In Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track, pages 173–182, Macau SAR, China. Asia-Pacific Association for Machine Translation.
Cite (Informal):
Brand Consistency for Multilingual E-commerce Machine Translation (Zhang et al., MTSummit 2023)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-acl-2023-videos/2023.mtsummit-users.17.pdf