RTM results for Predicting Translation Performance

Ergun Biçici


Abstract
With improved prediction combination using weights based on their training performance and stacking and multilayer perceptrons to build deeper prediction models, RTMs become the 3rd system in general at the sentence-level prediction of translation scores and achieve the lowest RMSE in English to German NMT QET results. For the document-level task, we compare document-level RTM models with sentence-level RTM models obtained with the concatenation of document sentences and obtain similar results.
Anthology ID:
W18-6458
Volume:
Proceedings of the Third Conference on Machine Translation: Shared Task Papers
Month:
October
Year:
2018
Address:
Belgium, Brussels
Venues:
EMNLP | WMT | WS
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
765–769
Language:
URL:
https://www.aclweb.org/anthology/W18-6458
DOI:
10.18653/v1/W18-6458
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-6458.pdf