[PDF] Top 20 Lattice Based Transformer Encoder for Neural Machine Translation
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Lattice Based Transformer Encoder for Neural Machine Translation
... Our work is related to the source side representations for NMT. Generally, the NMT model uses the word as a basic unit for source sentences modeling. In order to obtain better source side representations and avoid OOV ... See full document
8
Incorporating Source Syntax into Transformer Based Neural Machine Translation
... into neural machine translation without requiring a specific NMT ...single encoder and different decoders to train two tasks: parsing the source sentence and translating from source to ...for ... See full document
10
On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
... Neural machine translation is a relatively new approach to statistical machine trans- lation based purely on neural ...The neural machine translation models ... See full document
9
Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder
... convolutional neural networks and temporal sharing for the transition functions in recurrent neural networks (Goodfellow et ...the encoder and decoder of an NMT ... See full document
8
Graph Based Translation Memory for Neural Machine Translation
... a translation graph (i.e. lattice) generated by SMT by rewarding the words which have high posterior probabilities over the ...a lattice generated by SMT to constrain the decoding space and rerank to ... See full document
8
Neural Lattice Search for Domain Adaptation in Machine Translation
... for neural machine translation ...stack-based lattice search al- gorithm for NMT and show that constrain- ing its search space with lattices gener- ated by phrase-based ... See full document
6
Character based Neural Machine Translation
... the neural MT baseline system from (Bahdanau et ...an encoder-decoder architecture with atten- tion, and introduce elements from the character- based neural language model (Kim et ...The ... See full document
5
UdS Submission for the WMT 19 Automatic Post Editing Task
... in machine translation ...2019. Based on recent research on the APE task (Junczys-Dowmunt and Grundkiewicz, 2018) and an architecture for the utilization of document- level context information in ... See full document
6
Memory enhanced Decoder for Neural Machine Translation
... function is a highly non-convex function of the parameters with more complicated land- scape than that for decoder without exter- nal memory, rendering direct optimization over all the parameters rather difficult. ... See full document
9
Improved Neural Machine Translation with a Syntax Aware Encoder and Decoder
... Most neural machine translation (NMT) models are based on the sequential encoder-decoder framework, which makes no use of syntactic ...tree encoder which learns both sequential ... See full document
10
Recycling a Pre trained BERT Encoder for Neural Machine Translation
... a machine translation system us- ing two XLM models as the encoder and ...to neural machine translation (NMT) based on the Transformer (Vaswani et ...the ... See full document
9
A Character Aware Encoder for Neural Machine Translation
... To our surprise, the character-aware NMT model is able to translate the name entity very well, as shown in table 4. According to table 4, we can see that the proposed model achieves better translation performance ... See full document
8
An Analysis of Encoder Representations in Transformer Based Machine Translation
... the Transformer architecture for the MT task, we have to note that each model is trained using full word forms in order to facilitate the anal- ysis of the encoder representation (our results are in line ... See full document
11
Transformer Dissection: An Unified Understanding for Transformer’s Attention via the Lens of Kernel
... on neural machine translation (NMT) and sequence prediction (SP) tasks since these two tasks are commonly cho- sen for studying Transformers (Vaswani et ...(e.g., encoder self-attention, ... See full document
10
Cross Corpora Evaluation and Analysis of Grammatical Error Correction Models — Is Single Corpus Evaluation Enough?
... three neural machine translation (NMT)- based models (LSTM, CNN, and transformer) and a statistical machine translation (SMT)- based model is evaluated against six ... See full document
6
Understanding Neural Machine Translation by Simplification: The Case of Encoder-free Models
... Neural machine translation (NMT) (Kalchbrenner and Blunsom, 2013; Sutskever et ...employ encoder-decoder architec- tures where an encoder encodes source-side sen- tences and an ... See full document
8
Multi Source Transformer for Kazakh Russian English Neural Machine Translation
... We trained en2kk, ru2kk and en2ru SMT sys- tems using Portage (Larkin et al., 2010), a conven- tional log-linear phrase-based SMT system, us- ing the corresponding BPEed parallel corpora pre- pared as described in ... See full document
8
Montreal Neural Machine Translation Systems for WMT’15
... are based on the encoder- decoder architecture (Cho et ...the encoder, which compresses it into a real-valued ...the encoder assigns a context-dependent vector, or annotation, to every source ... See full document
7
A Convolutional Encoder Model for Neural Machine Translation
... to neural machine translation relies on bi-directional LSTMs to encode the source ...architecture based on a succession of convolutional ...Romanian translation we achieve compet- itive ... See full document
13
Alignment Based Neural Machine Translation
... the translation probability depending on an intermediate compu- tation of an alignment ...e.g. neural models, count-based models, ...the translation score is based on the alignment ... See full document
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