How Robust Are Character-Based Word Embeddings in Tagging and MT Against Wrod Scramlbing or Randdm Nouse?

Georg Heigold, Stalin Varanasi, Günter Neumann, Josef van Genabith


Anthology ID:
W18-1807
Volume:
Proceedings of the 13th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)
Month:
March
Year:
2018
Address:
Boston, MA
Editors:
Colin Cherry, Graham Neubig
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
68–80
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/W18-1807/
DOI:
Bibkey:
Cite (ACL):
Georg Heigold, Stalin Varanasi, Günter Neumann, and Josef van Genabith. 2018. How Robust Are Character-Based Word Embeddings in Tagging and MT Against Wrod Scramlbing or Randdm Nouse?. In Proceedings of the 13th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), pages 68–80, Boston, MA. Association for Machine Translation in the Americas.
Cite (Informal):
How Robust Are Character-Based Word Embeddings in Tagging and MT Against Wrod Scramlbing or Randdm Nouse? (Heigold et al., AMTA 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/W18-1807.pdf