In this paper, we present an improved
graph-based translation model which segments an input graph into node-induced
subgraphs by taking source context into
consideration. Translations are generated
by combining subgraph translations leftto-right using beam search. Experiments
on Chinese–English and German–English
demonstrate that the context-aware segmentation significantly improves the baseline
graph-based model.
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers.
.
Association for Computational Linguistics.
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Funders:
European Union’s Horizon 2020 research and innovation programme under grant agreement no 645452 (QT21)., ADAPT Centre for Digital Content Technology is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is cofunded under the European Regional Development Fund
ID Code:
23332
Deposited On:
21 May 2019 15:44 by
Thomas Murtagh
. Last Modified 21 May 2019 15:44