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From feature to paradigm: Deep learning in machine translation (Extended Abstract)

Author
Ruiz, M.
Type of activity
Presentation of work at congresses
Name of edition
27th International Joint Conference on Artificial Intelligence, IJCAI 2018
Date of publication
2018
Presentation's date
2018-07-13
Book of congress proceedings
IJCAI International Joint Conference on Artificial Intelligence
Repository
http://hdl.handle.net/2117/125670 Open in new window
Abstract
n 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-de...
Citation
Ruiz, M. From feature to paradigm: Deep learning in machine translation (Extended Abstract). A: International Joint Conference on Artificial Intelligence. "IJCAI International Joint Conference on Artificial Intelligence". 2018.
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
TALP - Centre for Language and Speech Technologies and Applications
VEU - Speech Processing Group

Participants