[PDF] Top 20 Alignment Based Neural Machine Translation

... the translation probability depending on an intermediate compu- tation of an alignment ...The alignment distribution is used to choose the positions in the source sentence that the decoder attends to ... See full document

... uses neural models trained using explicit hard alignments to generate ...explicit alignment modeling, making them more convenient for tasks where the source-to- target alignment is ...for ... See full document

... the translation model that take the full source sentence into ...and alignment prob- abilities in the HMM are modeled using feed- forward neural networks (FFNN) and they are trained ... See full document

... Cohn et al., 2016; Meng et al., 2016; Wang et al., 2016) that concentrate on the improve- ment of the attention mechanism. To remit the computing cost of the attention mecha- nism when dealing with long sentences, Lu- ... See full document

... hand, alignment mistakes are often generated when many Korean words with different morphologies are aligned with the same Chinese tokens in Korean-Chinese ...an alignment–based word reordering method ... See full document

... improve neural machine transla- tion (NMT) by selectively focusing on parts of the source sentence during trans- ...WMT translation tasks between English and German in both ... See full document

... than Google Translate with generic domain corpora, and were not statistically significantly different for English→Simplified Chinese. Unsurprisingly, the in-domain medical domain English-Spanish mod- els outperformed ... See full document

... training procedure, and the hyperparameters as our proposed models, but has a word-based de- coder. We trained this system on the training data without chunk segmentations (the second line in Table 3) and with ... See full document

... that those regional visual attributes would assist LSTM to generate better and more accurate repre- sentations. The illustration of the proposed model is depicted in 3. We will first explain how to deter- mine multiple ... See full document

... of neural machine translation, we combine a neural language model with a con- textual input ...soft alignment over the input text to help inform the summary (as shown in Figure ... See full document

... built based on the previously proposed unsupervised MT sys- tems, with some adaptations made to accom- modate the morphologically rich characteristics of German and Czech (Tsarfaty et ...subword-level ... See full document

... The goal of this work is to combine the advantages of neural and phrase-based machine translation systems. Handling of rare words is an essential aspect to consider when it comes to real-world ... See full document

... 2009). Machine learn- ing models are typically trained using stochastic gradient descent methods, by uniformly sampling mini-batches from the pool of training examples, and using them to compute updates for the ... See full document

... chunk alignment from Chinese-English parallel ...chunk alignment (Zhou ...chunk alignment; they used an SMT based model for chunk translation and then aligned the source- target chunk ... See full document

... a translation dictionary to improve statis- tical word alignment?” Compared with a transla- tion dictionary, the advantages of a rule-based machine translation system lie in two ... See full document

... Statistical Machine Translation (SMT) is based on alignment models which learn from bilingual corpora the word correspondences between the source and target ...Recursive Alignment Block ... See full document

... phrase based statisti- cal translation model has been developed which has been trained with the same EILMT tourism domain corpus of 22,492 ...rule based event actor alignments are validated by ... See full document

... attention based neural network for image caption task and ad- vance the state-of-the-art results; Yin et ...of machine translation, the idea of attention based neu- ral networks has ... See full document

... Sharing Latent Representations: A shared en- coder representation acts like an interlingua, which is translated in the decoder target language regardless of the input source language. This ensures that the benefits of ... See full document

... This paper proposes a new attention mechanism for NMT based on convolutional neural networks (CNNs) to leverage the structures of source sen- tences in NMT without parsing. In the parsing field, the CKY ... See full document