132 citations · 186 across the 15 of their papers we have counts for
15 papers
Using Multiple Subwords to Improve English-Esperanto Automated Literary Translation Quality
Alberto Poncelas, Jan Buts, James Hadley +1
Building Machine Translation (MT) systems for low-resource languages remains challenging. For many language pairs, parallel data are not widely available, and in such cases MT mode…
The Impact of Indirect Machine Translation on Sentiment Classification
Alberto Poncelas, Pintu Lohar, Andy Way +1
Sentiment classification has been crucial for many natural language processing (NLP) applications, such as the analysis of movie reviews, tweets, or customer feedback. A sufficient…
Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation
Xabier Soto, Dimitar Shterionov, Alberto Poncelas +1
Machine translation (MT) has benefited from using synthetic training data originating from translating monolingual corpora, a technique known as backtranslation. Combining backtran…
Facilitating Access to Multilingual COVID-19 Information via Neural Machine Translation
Andy Way, Rejwanul Haque, Guodong Xie +3
Every day, more people are becoming infected and dying from exposure to COVID-19. Some countries in Europe like Spain, France, the UK and Italy have suffered particularly badly fro…
Multiple Segmentations of Thai Sentences for Neural Machine Translation
Alberto Poncelas, Wichaya Pidchamook, Chao-Hong Liu +2
Thai is a low-resource language, so it is often the case that data is not available in sufficient quantities to train an Neural Machine Translation (NMT) model which perform to a h…
A Tool for Facilitating OCR Postediting in Historical Documents
Alberto Poncelas, Mohammad Aboomar, Jan Buts +2
Optical character recognition (OCR) for historical documents is a complex procedure subject to a unique set of material issues, including inconsistencies in typefaces and low quali…
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…
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…
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…
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…
The ADAPT System Description for the IWSLT 2018 Basque to English Translation Task
Alberto Poncelas, Andy Way, Kepa Sarasola
In this paper we present the ADAPT system built for the Basque to English Low Resource MT Evaluation Campaign. Basque is a low-resourced, morphologically-rich language. This poses…
Data Selection with Feature Decay Algorithms Using an Approximated Target Side
Alberto Poncelas, Gideon Maillette de Buy Wenniger, Andy Way
Data selection techniques applied to neural machine translation (NMT) aim to increase the performance of a model by retrieving a subset of sentences for use as training data. One o…
Understanding Meanings in Multilingual Customer Feedback
Chao-Hong Liu, Declan Groves, Akira Hayakawa +2
Understanding and being able to react to customer feedback is the most fundamental task in providing good customer service. However, there are two major obstacles for international…
Investigating Backtranslation in Neural Machine Translation
Alberto Poncelas, Dimitar Shterionov, Andy Way +2
A prerequisite for training corpus-based machine translation (MT) systems -- either Statistical MT (SMT) or Neural MT (NMT) -- is the availability of high-quality parallel data. Th…