[PDF] Top 20 Neural Machine Translation with Reordering Embeddings
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Neural Machine Translation with Reordering Embeddings
... the machine translation ...positional embeddings by a positional encoding mechanism (Gehring et ...predict translation, and has delivered state-of-the-art performance on various ... See full document
13
Unsupervised Domain Adaptation for Neural Machine Translation with Domain Aware Feature Embeddings
... In this work, we propose a simple yet effective un- supervised domain adaptation technique for neu- ral machine translation, which adapts the model by domain-aware feature embeddings learned with ... See full document
6
Non projective Dependency based Pre Reordering with Recurrent Neural Network for Machine Translation
... the reordering framework described above, we could try to directly predict the ex- ecutions as Miceli Barone and Attardi (2013) attempted with their version of the frame- ... See full document
11
Non projective Dependency based Pre Reordering with Recurrent Neural Network for Machine Translation
... Yaser Al-Onaizan and Kishore Papineni. 2006. Dis- tortion models for statistical machine translation. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual ... See full document
11
When and Why Are Pre Trained Word Embeddings Useful for Neural Machine Translation?
... pre-trained embeddings in providing a better representations of less frequent concepts when used with low-resource ...trained embeddings substitutes these phrases for common ones (“i”), drops them entirely, ... See full document
7
Improving Word Sense Disambiguation in Neural Machine Translation with Sense Embeddings
... sense embeddings and include the resulting sense labels into the NMT model as additional in- put features (Alexandrescu and Kirchhoff, 2006; Sennrich and Haddow, ... See full document
9
Learning to Generate Word and Phrase Embeddings for Efficient Phrase Based Neural Machine Translation
... Neural machine translation (NMT) often fails in one-to-many translation, ...the translation of phrases, phrase-based NMT systems have been proposed; these typically combine word- based ... See full document
8
Beyond Weight Tying: Learning Joint Input Output Embeddings for Neural Machine Translation
... word embeddings. Our evaluation shows that the structure-aware output layer outperforms weight tying in all cases and maintains a significant dif- ference with the typical output layer without com- promising much ... See full document
11
Quality Estimation with Force Decoded Attention and Cross lingual Embeddings
... a neural machine translation (NMT) ...any translation output, without access to the translation system that produced the translations in ... See full document
6
ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems
... of machine translation (MT) ...ral machine translation (NMT): based on encoder- decoder architectures (also known as seq2seq), NMT can use recurrent neural networks (RNNs) (Sutskever et ... See full document
7
A Neural Reordering Model for Phrase based Translation
... the machine translation system and neu- ral classifier are trained separately, the neural network training only has an indirect effect on translation ...the machine translation ... See full document
11
Morphological Word Embeddings for Arabic Neural Machine Translation in Low Resource Settings
... Other work uses purely unsupervised techniques. Luong et al. (2013) segment words using Morfes- sor (Creutz and Lagus, 2007), and use recursive neural networks to build word embeddings from morph ... See full document
11
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
... English-Indonesian Neural Machine Translation for Spoken Language Domains Meisyarah Dwiastuti.. Improving Neural Entity Disambiguation with Graph Embeddings Özge Sevgili, Alexander Panch[r] ... See full document
20
Shared Private Bilingual Word Embeddings for Neural Machine Translation
... English-German translation task, as shown in Ta- ble ...their translation quality ...well-trained embeddings to distinguish the homographs of sub- ...target embeddings benefit from the shared ... See full document
10
Incorporating Word Reordering Knowledge into Attention based Neural Machine Translation
... word reordering knowledge through estimating the probability distribu- tion of relative jump distances on source words to incorporate word reordering knowledge into the attention-based ... See full document
11
Exploring the use of Acoustic Embeddings in Neural Machine Translation
... This work focuses on the integration of auxiliary features extracted from audio accompanying the text. Whilst features extracted from text and images have been explored, the use of audio information for NMT remains an ... See full document
9
LSTM Neural Reordering Feature for Statistical Machine Translation
... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Con- stantin, and Evan ... See full document
6
Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques
... proper translation has to be derived from ...the translation sys- tem is gender biased, the context is disregarded, while if the system is neutral, the translation is cor- rect (since it has the ... See full document
8
Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings
... NMT translation, in our new bridging approach we do not use extra re- sources in the NMT model, but let the model itself learn the similarity of word pairs from the training ... See full document
10
A Word Reordering Model for Improved Machine Translation
... our reordering models we need training data where we have the input source language sentence and the desired reordering in the target ...English reordering as the source of the word alignments is ... See full document
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