[PDF] Top 20 Neural Machine Translation with Extended Context

... previous translation unit to the sentence to be translated and mark all tokens (BPE seg- ments in our case) with a special prefix (cc ) to indicate that they come from contextual informa- ...marked context ... See full document

... Standard machine translation systems pro- cess sentences in isolation and hence ig- nore extra-sentential information, even though extended context can both prevent mistakes in ambiguous cases ... See full document

... attention neural machine translation model can be benefit by constraining the attentional process to adequately cover the source words (Sankaran et ...attentional neural net- work. Our ... See full document

... include context of the gender of the ambiguous “friend” in the English-Spanish trans- ...proper translation has to be derived from ...the translation sys- tem is gender biased, the context is ... See full document

... en → ja models The additional data did not con- tribute to the translation quality, which indicates that the data augmentation using back-translation was not effective. This is partly due to difficult ja→en ... See full document

... Document-level machine translation (MT) re- mains challenging due to the difficulty in effi- ciently using document context for ...global context for document- level neural ... See full document

... document- context on both source and target-side using mem- ory networks (Maruf and Haffari, ...previous context to use and there has been no comparison between the online and offline setting except using ... See full document

... pronoun translation are reference-based meth- ods that produce a score based on word alignment between source, translation output, and reference translation, and identification of pronouns in them, ... See full document

... In this context, it was also claimed that PE was killing translators’ creativity. The word ‘cre- ativity’ seemed to be used here in the sense of being able to produce a new text, a process ac- companied by ... See full document

... land machine translation systems submit- ted to the WMT17 German-English Ban- dit Learning ...a translation system to a new domain, using only bandit feedback: the system receives a German sentence ... See full document

... convolutional neural machine translation without this bottleneck was first achieved in Kaiser and Bengio (2016) and Kalchbrenner et ...(Extended Neural GPU) used a recurrent stack of ... See full document

... One main drawback of this approach is that the whole source sentence has to be stored in a fixed- size context vector. To overcome this problem, (Bahdanau et al., 2014) introduced the soft attention mechanism. ... See full document

... The results are shown in the lower part of Ta- ble 3. Context encoding without any sequenti- al modeling (the last row) shows indeed compa- rable performance to using a full 6-layer enco- der. This simplified ... See full document

... Auxiliary Context mechanism for in- corporating cross-sentence context, there are two main differences: 1) we have separate parameters to better control the effects of the cross- and intra- sentence ... See full document

... granularity translation unit from words to smaller subwords or ...recurrent neural networks, thus achieving open vocabulary ...methods extended the vocabulary to a larger or unlimited vocabulary and ... See full document

... general translation quality, allowing to rank them as ...the translation from the fused sys- tem is better than the baseline, and they consider the quality of both translations to tie 19% of the ... See full document

... side context, which are summarized into a senten- tial context ...source-side context vector is fed to the decoder, so that translation at each step is conditioned on the whole source-side ... See full document

... document-level neural machine translation model in C++ using the DyNet li- brary (Neubig et ...The translation model uses GRU units for the bidi- rectional RNN encoder and the 2-layer RNN de- ... See full document

... Figure 2(b) shows the results of manual evalu- ation on 200 source sentences randomly sampled from the test sets. Reducing the effect of source con- text (i.e., (0.8, 1.0) and (0.5, 1.0)) leads to more flu- ent yet less ... See full document

... Our proposed model can encode not only the sen- tence to be translated but also its preceding and succeeding sentences together, based on the re- sults of coreference resolution. Therefore, infor- mation about sentence ... See full document