Článek ve sborníku konference

MATĚJKA Pavel, GLEMBEK Ondřej, NOVOTNÝ Ondřej, PLCHOT Oldřich, GRÉZL František, BURGET Lukáš a ČERNOCKÝ Jan. Analysis Of DNN Approaches To Speaker Identification. In: Proceedings of the 41th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), 2016. Shanghai: IEEE Signal Processing Society, 2016, s. 5100-5104. ISBN 978-1-4799-9988-0.
Jazyk publikace:angličtina
Název publikace:Analysis Of DNN Approaches To Speaker Identification
Název (cs):Analýza DNN přístupů k identifikaci mluvčího
Strany:5100-5104
Sborník:Proceedings of the 41th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), 2016
Konference:41th IEEE International Conference on Acoustics, Speech and Signal Processing
Místo vydání:Shanghai, CN
Rok:2016
ISBN:978-1-4799-9988-0
Vydavatel:IEEE Signal Processing Society
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2016/matejka_icassp2016_0005100.pdf [PDF]
Klíčová slova
automatic speaker identification, deep neural networks, bottleneck features, i-vector
Anotace
Článek pojednává o analýze Deep Neural Networks přístupů k identifikaci mluvčího. Analyzovali jsme systémy založené na i-vektorech pomocí DNN Bottleneck příznaků.
Abstrakt
This work studies the usage of the Deep Neural Network (DNN) Bottleneck (BN) features together with the traditional MFCC features in the task of i-vector-based speaker recognition. We decouple the sufficient statistics extraction by using separate GMM models for frame alignment, and for statistics normalization and we analyze the usage of BN and MFCC features (and their concatenation) in the two stages. We also show the effect of using full-covariance GMM models, and, as a contrast, we compare the result to the recent DNNalignment approach. On the NIST SRE2010, telephone condition, we show 60% relative gain over the traditional MFCC baseline for EER (and similar for the NIST DCF metrics), resulting in 0.94% EER.
BibTeX:
@INPROCEEDINGS{
   author = {Pavel Mat{\v{e}}jka and Ond{\v{r}}ej Glembek and
	Ond{\v{r}}ej Novotn{\'{y}} and Old{\v{r}}ich
	Plchot and Franti{\v{s}}ek Gr{\'{e}}zl and
	Luk{\'{a}}{\v{s}} Burget and Jan
	{\v{C}}ernock{\'{y}}},
   title = {Analysis Of DNN Approaches To Speaker
	Identification},
   pages = {5100--5104},
   booktitle = {Proceedings of the 41th IEEE International Conference on
	Acoustics, Speech and Signal Processing (ICASSP 2016), 2016},
   year = {2016},
   location = {Shanghai, CN},
   publisher = {IEEE Signal Processing Society},
   ISBN = {978-1-4799-9988-0},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.cs?id=11140}
}

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