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Neural network language models to select the best translation

Autor
Khalilov, M.; Fonollosa, José A. R.; Zamora-Martínez, F.; Castro-Bleda, M.J.; España-Boquera, S.
Tipus d'activitat
Article en revista
Revista
Computational Linguistics in the Netherlands Journal
Data de publicació
2013-12-20
Volum
3
Pàgina inicial
217
Pàgina final
233
Repositori
http://hdl.handle.net/2117/21106 Obrir en finestra nova
URL
http://clinjournal.org/sites/default/files/13-Khalilov-etal-CLIN2013.pdf Obrir en finestra nova
Resum
The quality of translations produced by statistical machine translation (SMT) systems crucially depends on the generalization ability provided by the statistical models involved in the process. While most modern SMT systems use n-gram models to predict the next element in a sequence of tokens, our system uses a continuous space language model (LM) based on neural networks (NN). In contrast to works in which the NN LM is only used to estimate the probabilities of shortlist words (Schwenk 2010), w...
Citació
Khalilov, M. [et al.]. Neural network language models to select the best translation. "Computational Linguistics in the Netherlands Journal", 20 Desembre 2013, vol. 3, p. 217-233.
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

  • Khalilov, Maxim  (autor)
  • Rodríguez Fonollosa, José Adrián  (autor)
  • Zamora Martínez, Francisco  (autor)
  • Castro Bleda, María José  (autor)
  • España Boquera, Salvador  (autor)

Arxius