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From feature to paradigm: deep learning in machine translation

Autor
Ruiz, M.
Tipus d'activitat
Article en revista
Revista
Journal of artificial intelligence research
Data de publicació
2018-04-01
Volum
61
Pàgina inicial
947
Pàgina final
974
Repositori
http://hdl.handle.net/2117/116854 Obrir en finestra nova
URL
https://jair.org/index.php/jair/article/view/11198 Obrir en finestra nova
Resum
In the last years, deep learning algorithms have highly revolutionized several areas including speech, image and natural language processing. The specific field of Machine Translation (MT) has not remained invariant. Integration of deep learning in MT varies from re-modeling existing features into standard statistical systems to the development of a new architecture. Among the different neural networks, research works use feed- forward neural networks, recurrent neural networks and the encoder-d...
Citació
Ruiz, M. From feature to paradigm: deep learning in machine translation. "Journal of artificial intelligence research", 1 Abril 2018, vol. 61, p. 947-974.
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
TALP - Centre de Tecnologies i Aplicacions del Llenguatge i la Parla
VEU - Grup de Tractament de la Parla

Participants

Arxius