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GRÉZL, F. KARAFIÁT, M. VESELÝ, K.
Original Title
Adaptation of Multilingual Stacked Bottle-neck Neural Network Structure for New Language
Type
conference paper
Language
English
Original Abstract
In this paper a multilingual training of Stacked Bottle- Neck neural network structure for feature extraction is addressed. While for languages with plentiful resources, the optimal approach is to train the BN-NN on the target data, limited resources call for re-using data from other languages.
Keywords
feature extraction, Bottle-neck features, neural network adaptation, multilingual neural networks, Stacked Bottle- Neck structure
Authors
GRÉZL, F.; KARAFIÁT, M.; VESELÝ, K.
RIV year
2014
Released
4. 5. 2014
Publisher
IEEE Signal Processing Society
Location
Florencie
ISBN
978-1-4799-2892-7
Book
Proceedings of ICASSP 2014
Pages from
7704
Pages to
7708
Pages count
5
URL
http://www.fit.vutbr.cz/research/groups/speech/publi/2014/grezl_icassp2014_p7704_adapation.pdf
BibTex
@inproceedings{BUT111544, author="František {Grézl} and Martin {Karafiát} and Karel {Veselý}", title="Adaptation of Multilingual Stacked Bottle-neck Neural Network Structure for New Language", booktitle="Proceedings of ICASSP 2014", year="2014", pages="7704--7708", publisher="IEEE Signal Processing Society", address="Florencie", doi="10.1109/ICASSP.2014.6855089", isbn="978-1-4799-2892-7", url="http://www.fit.vutbr.cz/research/groups/speech/publi/2014/grezl_icassp2014_p7704_adapation.pdf" }