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Title: Machine Translation Between High-resource Languages in a Language Documentation Setting
Language documentation encompasses translation, typically into the dominant high-resource language in the region where the target language is spoken. To make data accessible to a broader audience, additional translation into other high-resource languages might be needed. Working within a project documenting Kotiria, we explore the extent to which state-of-the-art machine translation (MT) systems can support this second translation – in our case from Portuguese to English. This translation task is challenging for multiple reasons: (1) the data is out-of-domain with respect to the MT system’s training data, (2) much of the data is conversational, (3) existing translations include non-standard and uncommon expressions, often reflecting properties of the documented language, and (4) the data includes borrowings from other regional languages. Despite these challenges, existing MT systems perform at a usable level, though there is still room for improvement. We then conduct a qualitative analysis and suggest ways to improve MT between high-resource languages in a language documentation setting.  more » « less
Award ID(s):
1664348
NSF-PAR ID:
10387783
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Proceedings International Conference on Computational Linguistics
ISSN:
1525-2477
Page Range / eLocation ID:
26-33
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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