DocumentCode
1748778
Title
Part-of-speech tagging with recurrent neural networks
Author
Pérez-Ortiz, Juan Antonio ; Forcada, Mikel L.
Author_Institution
Dept. de Llenguatges i Sistemes Inf., Alacanti Univ., Spain
Volume
3
fYear
2001
fDate
2001
Firstpage
1588
Abstract
Explores the use of discrete-time recurrent neural networks for part-of-speech disambiguation of textual corpora. Our approach does not need a hand-tagged text for training the tagger, being probably the first neural approach doing so. Preliminary results show that the performance of this approach is, at least, similar to that of a standard hidden Markov model trained using the Baum-Welch algorithm
Keywords
learning (artificial intelligence); natural languages; recurrent neural nets; discrete-time recurrent neural networks; part-of-speech disambiguation; part-of-speech tagging; textual corpora; Books; Hidden Markov models; Natural language processing; Natural languages; Recurrent neural networks; Speech; Statistics; Tagging;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-7044-9
Type
conf
DOI
10.1109/IJCNN.2001.938396
Filename
938396
Link To Document