Low-Resource NMT: an Empirical Study on the Effect of Rich Morphological Word Segmentation on Inuktitut

Tan Ngoc Le, Fatiha Sadat


Anthology ID:
2020.amta-research.15
Volume:
Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)
Month:
October
Year:
2020
Address:
Virtual
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
165–172
Language:
URL:
https://aclanthology.org/2020.amta-research.15
DOI:
Bibkey:
Cite (ACL):
Tan Ngoc Le and Fatiha Sadat. 2020. Low-Resource NMT: an Empirical Study on the Effect of Rich Morphological Word Segmentation on Inuktitut. In Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), pages 165–172, Virtual. Association for Machine Translation in the Americas.
Cite (Informal):
Low-Resource NMT: an Empirical Study on the Effect of Rich Morphological Word Segmentation on Inuktitut (Le & Sadat, AMTA 2020)
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PDF:
https://preview.aclanthology.org/auto-file-uploads/2020.amta-research.15.pdf
Code
 ngoctanle/inuktitut-english-nmt