[PDF] Top 20 Context Aware Neural Machine Translation Decoding

... sophisticated context- aware approaches propose to modify the NMT ar- ...as context sentence the previous source sentence, showing how NMT systems can also benefit from larger ...sentence ... See full document

... of a word and its position in a sentence. Since the original BoW encoder captures the linear order- ing information only in a very crude way (through the position embeddings), the structural informa- tion provided by GCN ... See full document

... chine translation (SMT), neural machine translation (NMT) often sacrifices ade- quacy for the sake of ...phrase-based decoding cost for an NMT output and then using this cost to rerank ... See full document

... Though widely used, length normalization is not a perfect solution. NMT systems stil- l have under-translation and over-translation prob- lem even with a normalized model. It is due to the lack of the ... See full document

... of translation, these mechanisms work at the word level and cannot capture phrasal cohe- sion between the two languages (Fox, 2002; Kim et ...the translation more in line with the source syntactic ...rect ... See full document

... sentential context for neural machine translation ...sentential context extracted from the top encoder layer only, can improve translation performance via contextualizing the ... See full document

... Compared to previous lexical selection models, CATM jointly models both local contextual words and global topics. Such a joint modeling also en- ables CATM to capture their inner correlations at the model level. In order ... 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

... larger translation units. Here, the neural network produces a translation of the entire ex- tended ...External context is not marked with specific prefixes anymore and token represen- tations ... See full document

... slow translation speed, especially when it works not on GPUs, but on CPUs, which are more com- mon ...the translation, the widely used method is to trade off between the translation quality and the ... See full document

... At the same time, some researchers propose to use an additional set of an encoder and attention to model more information. For example, Jean et al. (2017) use it to encode and select part of the previous source sentence ... See full document

... To shrink the run-time target vocabulary, our first method uses Locality Sensitive Hashing. Vi- jayanarasimhan et al. (2015) successfully applies it on CPUs and gains speedup on single step prediction tasks such as image ... See full document

... Since the smallest units of text data are characters, character-based approaches have been introduced into the fields of NMT. Costa-juss`a and Fonollosa (2016) have shown that the character-based encoding by using ... See full document

... diverse translation quality, in particu- lar Rel with refined position encoding achieves the best ...in decoding stage, which indicates its practicability in deploy- ... See full document

... To the best of our knowledge, there is no pub- licly available parallel corpus of named entities. In order to create one, we downloaded the OpenSub- titles database (Lison and Tiedemann, 2016) for German and English and ... See full document

... in neural machine translation ...English-Vietnamese translation tasks, re- ...Chinese-English translation and 0.80 point for English-Vietnamese translation, ... See full document

... Shortly, the contributions of this paper can be summarized as follow: The N-best results of SMT are regarded as a candidate list of suspicious word, which is reranked by using a discourse-aware reranking system. ... See full document

... document-level neural ma- chine translation model which takes both source and target document context into account using memory ...a neural translation model equipped with two memory ... See full document

... Though machine translation errors caused by the lack of context beyond one sentence have long been acknowledged, the development of context-aware NMT systems is hampered by several ... See full document

... of neural machine transla- tion starts with training a model to maximize its ...reference translation given a source sentence over a large par- allel ...of translation becomes equivalent to ... See full document