[PDF] Top 20 A Character level Decoder without Explicit Segmentation for Neural Machine Translation
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A Character level Decoder without Explicit Segmentation for Neural Machine Translation
... Why Character-Level Translation? Why not Word-Level Translation? The most pressing issue with word-level processing is that we do not have a perfect word segmentation al- ... See full document
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Fully Character Level Neural Machine Translation without Explicit Segmentation
... fully character-level NMT model that maps a character sequence in a source language to a character sequence in a target ...purely character-level NMT model with a basic encoder ... See full document
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How Grammatical is Character level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairs
... trastive translation pairs for the assessment of neu- ral machine translation ...specific translation errors to the contrastive trans- lations, we gain valuable insight into the abil- ity of ... See full document
7
Plan, Attend, Generate: Character Level Neural Machine Translation with Planning
... on character-level translation tasks from WMT’15 for English to German, English to Finnish, and English to Czech language ...in neural character-level ... See full document
7
On the Importance of Word Boundaries in Character level Neural Machine Translation
... fully character-level (Cherry et ...the machine translation task from English into five languages from different language families and exhibiting distinct mor- phological typology: Arabic ... See full document
7
Character based Neural Machine Translation
... the neural MT baseline system from (Bahdanau et ...the character- based neural language model (Kim et ...The translation unit continues to be the word, and we continue using word embeddings ... See full document
5
A Character Aware Encoder for Neural Machine Translation
... the character-level NMT model to solve many scalability issues, both in terms of computational speed and memory ...each character occurs frequently in the training corpus, all of the character ... See full document
8
Chunk Based Bi Scale Decoder for Neural Machine Translation
... word level, packing the phrasal and lexi- cal information in one hidden state, which is not necessarily the best for ...fine-grained translation levels such as the character or sub-word levels, which ... See full document
7
Chunk based Decoder for Neural Machine Translation
... as machine translation (Luong and Manning, 2016), document modeling (Li et ...sentence-word level to obtain better document ...word-character level to cope with the out-of-vocabulary ... See full document
12
Combining Character and Word Information in Neural Machine Translation Using a Multi Level Attention
... most neural machine translation sys- tems require the sentence to be represented as a sequence at a single level of ...with character atten- tion which augments the ... See full document
10
Neural Machine Translation of Logographic Language Using Sub character Level Information
... are character level data without BPE segmentation, while “bpe” (character level), “ideograph”, and “stroke” (sub- character level) are data with BPE ... See full document
9
Improved Neural Machine Translation with a Syntax Aware Encoder and Decoder
... of translation, these mechanisms work at the word level and cannot capture phrasal cohe- sion between the two languages (Fox, 2002; Kim et ...With explicit syntactic structure, the decoder can ... See full document
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Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input
... Autoregressive Neural Machine Translation Deep neural network with encoder-decoder framework has achieved great success on machine translation, with differ- ent choices of ... See full document
8
Doubly Attentive Decoder for Multi modal Neural Machine Translation
... Multi-modal MT was just recently addressed by the MT community by means of a shared task (Specia et al., 2016). However, there has been a considerable amount of work on natu- ral language generation from non-textual ... See full document
12
Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder
... the decoder are significantly ...the decoder to perform reasonably well, without in- corporating high levels of morphological knowl- edge into the ... See full document
10
Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder
... in neural machine trans- lation (briefly, NMT) for similar languages ...German translation). The success of such word- level sharing motivates us to move one step further: we con- sider ... See full document
8
A Stochastic Decoder for Neural Machine Translation
... den state (or 512 for each direction in the bidirec- tional LSTMs) and 256 for the attention mechan- sim. Training is done with Adam (Kingma and Ba, 2015). In decoding we use a beam of size 5 and output the most likely ... See full document
10
Sentence Level Agreement for Neural Machine Translation
... of neural machine translation (NMT) is to minimize the loss between the words in the translated sentences and those in the ...entire neural network and the training objective is computed in ... See full document
7
Phrase Level Segmentation and Labelling of Machine Translation Errors
... Our labelling strategy is based on comparing the MT sen- tences and their version post-edited by a human, as it is done for labelling of word-level QE training data. This is only possible for labelling datasets at ... See full document
6
Document Level Adaptation for Neural Machine Translation
... its translation (acquired as described in Section ...ing machine translation model, this approach con- strains the search space to translations containing specified sub-sequences (in this case, the ... See full document
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