166 citations · 607 across the 32 of their papers we have counts for
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Selecting Artificially-Generated Sentences for Fine-Tuning Neural Machine Translation
Alberto Poncelas, Andy Way
Neural Machine Translation (NMT) models tend to achieve best performance when larger sets of parallel sentences are provided for training. For this reason, augmenting the training…
Getting Gender Right in Neural Machine Translation
Eva Vanmassenhove, Christian Hardmeier, Andy Way
Speakers of different languages must attend to and encode strikingly different aspects of the world in order to use their language correctly (Sapir, 1921; Slobin, 1996). One such d…
Combining SMT and NMT Back-Translated Data for Efficient NMT
Alberto Poncelas, Maja Popovic, Dimitar Shterionov +2
Neural Machine Translation (NMT) models achieve their best performance when large sets of parallel data are used for training. Consequently, techniques for augmenting the training…
Transductive Data-Selection Algorithms for Fine-Tuning Neural Machine Translation
Alberto Poncelas, Gideon Maillette de Buy Wenniger, Andy Way
Machine Translation models are trained to translate a variety of documents from one language into another. However, models specifically trained for a particular characteristics of…
Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translation
Eva Vanmassenhove, Dimitar Shterionov, Andy Way
This work presents an empirical approach to quantifying the loss of lexical richness in Machine Translation (MT) systems compared to Human Translation (HT). Our experiments show ho…
Adaptation of Machine Translation Models with Back-translated Data using Transductive Data Selection Methods
Alberto Poncelas, Gideon Maillette de Buy Wenniger, Andy Way
Data selection has proven its merit for improving Neural Machine Translation (NMT), when applied to authentic data. But the benefit of using synthetic data in NMT training, produce…
No Padding Please: Efficient Neural Handwriting Recognition
Gideon Maillette de Buy Wenniger, Lambert Schomaker, Andy Way
Neural handwriting recognition (NHR) is the recognition of handwritten text with deep learning models, such as multi-dimensional long short-term memory (MDLSTM) recurrent neural ne…
ABI Neural Ensemble Model for Gender Prediction Adapt Bar-Ilan Submission for the CLIN29 Shared Task on Gender Prediction
Eva Vanmassenhove, Amit Moryossef, Alberto Poncelas +2
We present our system for the CLIN29 shared task on cross-genre gender detection for Dutch. We experimented with a multitude of neural models (CNN, RNN, LSTM, etc.), more "traditio…