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Juan Antonio Pérez-Ortiz
Juan Antonio Pérez-Ortiz
Lecturer and researcher, Universitat d'Alacant, Spain
Bestätigte E-Mail-Adresse bei dlsi.ua.es
Titel
Zitiert von
Zitiert von
Jahr
Apertium: a free/open-source platform for rule-based machine translation
ML Forcada, M Ginestí-Rosell, J Nordfalk, J O’Regan, S Ortiz-Rojas, ...
Machine translation 25, 127-144, 2011
4732011
Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets
JA Pérez-Ortiz, FA Gers, D Eck, J Schmidhuber
Neural Networks 16 (2), 241-250, 2003
1572003
An open-source shallow-transfer machine translation engine for the Romance languages of Spain
AM Corbí-Bellot, ML Forcada, S Ortiz-Rojas, JA Pérez-Ortiz, ...
Proceedings of the 10th EAMT conference: practical applications of machine …, 2005
1092005
Open-source Portuguese–Spanish machine translation
C Armentano-Oller, RC Carrasco, AM Corbí-Bellot, ML Forcada, ...
International Workshop on Computational Processing of the Portuguese …, 2006
962006
Part-of-speech tagging with recurrent neural networks
JA Perez-Ortiz, ML Forcada
IJCNN'01. International Joint Conference on Neural Networks. Proceedings …, 2001
682001
Shallow parsing for Portuguese-Spanish machine translation
A Garrido Alenda, P Gilabert Zarco, JA Pérez-Ortiz, A Pertusa, ...
Ediçőes Colibri, 2004
412004
Using target-language information to train part-of-speech taggers for machine translation
F Sánchez-Martínez, JA Pérez-Ortiz, ML Forcada
Machine Translation 22, 29-66, 2008
332008
How neural machine translation works
JA Pérez-Ortiz, ML Forcada, F Sánchez-Martínez
Machine translation for everyone: Empowering users in the age of artificial …, 2022
282022
An open-source shallow-transfer machine translation toolbox: consequences of its release and availability
C Armentano-Oller, AM Corbí-Bellot, ML Forcada, M Ginestí-Rosell, ...
Workshop on open-source machine translation, 23-30, 2005
282005
Opentrad Apertium open-source machine translation system: an opportunity for business and research
G Ramírez Sánchez, F Sánchez-Martínez, S Ortiz Rojas, JA Pérez-Ortiz, ...
Aslib, 2006
242006
Rethinking data augmentation for low-resource neural machine translation: A multi-task learning approach
VM Sánchez-Cartagena, M Esplŕ-Gomis, JA Pérez-Ortiz, ...
arXiv preprint arXiv:2109.03645, 2021
222021
Online symbolic-sequence prediction with discrete-time recurrent neural networks
JA Pérez-Ortiz, J Calera-Rubio, ML Forcada
International Conference on Artificial Neural Networks, 719-724, 2001
212001
Apertium, una plataforma de código abierto para el desarrollo de sistemas de traducción automática
C Armentano Oller, AM Corbí Bellot, ML Forcada, M Ginestí Rosell, ...
Universidad de Cádiz. Servicio de Publicaciones, 2007
202007
A generalised alignment template formalism and its application to the inference of shallow-transfer machine translation rules from scarce bilingual corpora
VM Sanchez-Cartagena, JA Pérez-Ortiz, F Sánchez-Martínez
Computer Speech & Language 32 (1), 46-90, 2015
182015
Evaluating machine translation for assimilation via a gap-filling task
E Ageeva, ML Forcada, F Tyers, JA Pérez-Ortiz
Proceedings of the 18th Annual Conference of the European Association for …, 2015
182015
An open-source web-based tool for resource-agnostic interactive translation prediction
D Torregrosa Rivero, ML Forcada, JA Pérez-Ortiz
De Gruyter, 2014
162014
Integrating shallow-transfer rules into phrase-based statistical machine translation
VM Sánchez-Cartagena, F Sánchez-Martınez, JA Pérez-Ortiz
162011
ScaleMT: a free/open-source framework for building scalable machine translation web services
VM Sánchez-Cartagena, JA Pérez-Ortiz
Charles University in Prague. Institute of Formal and Applied Linguistics, 2010
162010
Learning context sensitive languages with LSTM trained with Kalman filters
FA Gers, JA Pérez-Ortiz, D Eck, J Schmidhuber
International Conference on Artificial Neural Networks, 655-660, 2002
162002
Online text prediction with recurrent neural networks
JA Pérez-Ortiz, J Calera-Rubio, ML Forcada
Neural processing letters 14, 127-140, 2001
152001
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