We participated in the WMT 2016 shared
news translation task on English ↔ Chinese language pair. Our systems are based
on the encoder-decoder neural machine
translation model with the attention mechanism. We employ the Gated Recurrent
Unit (GRU) with the linear associative
connection to build deep encoder and address the unknown words with the dictionary replace approach. The dictionaries are extracted from the parallel training data with unsupervised word alignment method. In the decoding procedure,
the translation probabilities of the target
word from different models are averagely
combined as the ensemble strategy. In this
paper, we introduce our systems from data
preprocessing to post-editing in details.
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Funders:
Science Foundation Ireland in the ADAPT Centre for Digital Content Technology (www.adaptcentre.ie) at Dublin City University funded under the SFI Research Centres Programme (Grant 13/RC/2106) co-funded under the European Regional Development Fund.
ID Code:
23331
Deposited On:
21 May 2019 08:28 by
Thomas Murtagh
. Last Modified 24 Jul 2019 14:20