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VESELÝ, K. KARAFIÁT, M. GRÉZL, F. JANDA, M. EGOROVA, E.
Original Title
The Language-Independent Bottleneck Features
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
The paper is about language-independent bottleneck features, which are generated by Multi-lingual Neural Network. This leads to features which are not biased towards any of the source languages, making the features effectively language independent.
Keywords
Language-Independent Bottleneck Features, Multilingual Neural Network
Authors
VESELÝ, K.; KARAFIÁT, M.; GRÉZL, F.; JANDA, M.; EGOROVA, E.
RIV year
2012
Released
5. 12. 2012
Publisher
IEEE Signal Processing Society
Location
Miami
ISBN
978-1-4673-5124-9
Book
Proceedings of IEEE 2012 Workshop on Spoken Language Technology
Pages from
336
Pages to
341
Pages count
6
URL
http://www.fit.vutbr.cz/research/groups/speech/publi/2012/vesely_slt2012_0000336.pdf
BibTex
@inproceedings{BUT97015, author="Karel {Veselý} and Martin {Karafiát} and František {Grézl} and Miloš {Janda} and Ekaterina {Egorova}", title="The Language-Independent Bottleneck Features", booktitle="Proceedings of IEEE 2012 Workshop on Spoken Language Technology", year="2012", pages="336--341", publisher="IEEE Signal Processing Society", address="Miami", doi="10.1109/SLT.2012.6424246", isbn="978-1-4673-5124-9", url="http://www.fit.vutbr.cz/research/groups/speech/publi/2012/vesely_slt2012_0000336.pdf" }