[PDF] Top 20 A Simple and Effective Approach to Coverage Aware Neural Machine Translation

... the coverage problem can be interpreted in a probability sto- ...the coverage score inter- pretable for different ...our coverage model is applied to every beam search step, while Wu et ...and ... See full document

... a machine transla- tion problem. The phrase table, i.e., translation model, consists of all possible character and character sequence ...statistical machine translation systems use a ... See full document

... improve neural machine transla- tion (NMT) by selectively focusing on parts of the source sentence during trans- ...two simple and effective classes of at- tentional mechanism: a global ... See full document

... granularity translation unit from words to smaller subwords or ...more effective approach to encode rare and unknown words as sequences of subword units by Byte Pair Encoding (Gage, ...recurrent ... See full document

... more effective as different embedding vectors of the ambiguous source word are learned, bet- ter capturing their different meaning employed in varying sentiment ...Although simple, our methods achieve ... See full document

... In this work, we present a novel and simple character-aware NMT model which encodes the input sentence at the character-level. In addition to be applied to the language that has a clear boundary between ... See full document

... propose simple, yet effective, cov- erage embedding models for attention-based ...special coverage embedding vec- tor for each source word to start with, and keeps up- dating those coverage ... See full document

... is based on RNNs and particularly on Tree Long Short Term Memory (Tree-LSTM) networks (Tai et al., 2015). LSTM (Hochreiter and Schmidhu- ber, 1997) is a sequence learning technique which uses a memory cell to preserve a ... See full document

... For the offline setting, however, there is only one work that effectively uses the full document- context on both source and target-side using mem- ory networks (Maruf and Haffari, 2018). The debate in document-level NMT ... See full document

... a simple and effective method for in- cluding target-side T-V annotation in the training of a neural machine translation (NMT) system, which allows us to control the level of politeness ... See full document

... the coverage model (Tu et al., 2016; Mi et al., 2016) provide effective mechanisms to control the generation of translation, these mechanisms work at the word level and cannot capture phrasal cohe- ... See full document

... our approach repeatedly scores the entire source for each target prefix, re- sulting in O(mn) ...our approach has greater time complexity, the practical differ- ence of scoring the tokens of a single source ... See full document

... a simple and effective ap- proach to incorporating syntactic struc- ture into neural attention-based encoder- decoder models for machine ...of neural networks developed for modeling ... See full document

... In this study, based on our hypothesis that the performance of context-aware models is more affected by the lack of the training data than sentence-level NMT models, we investigated the impact of large-scale ... See full document

... The existence of (small) perturbations that in- duce a critical prediction error in machine learn- ing models was first discovered and discussed in the field of image processing (Szegedy et al., 2014). Such ... See full document

... Second, different from the lexical models and relative frequencies that can be computed on both directions (source-to-target and target-to- source), a symmetric version of the context- awareness model cannot be ... See full document

... statistical machine transla- tion (SMT) and the ideas of this ...This approach, then, faces the same in- herent limitations as source-tokenization: do- main knowledge is required for ... See full document

... Table 1 shows the results 7 . In this table, we can observe that our proposed models, Cor-m and Cor-g, outperformed the baseline Concat in terms of BLEU scores at every unit length. Interestingly, at the setting of n = ... See full document

... first approach to context- aware machine translation using only monolin- gual document-level ...Our approach results in substantial improvements in translation quality as ... See full document

... Besides those discussed in Section 1, there are also some research on tuning sparse features on the train- ing data, but they integrate those sparse features into the MT log-linear model as a single feature weight, and ... See full document