Conference paper

KHOURY Elie S., VESNICER Boštjan, FRANCO-PEDROSO Javier, DIEZ Sánchez Mireia, CIPR Tomáš, SCHWARZ Petr, VAN Leeuwen David, PETROVSKA-DELACRETAZ Dijana, MATĚJKA Pavel, RODRIGUEZ-FUENTES Luis J., CHOLLET Gerard and MARCEL Sebastien et al. The 2013 Speaker Recognition Evaluation in Mobile Environment. In: Proceedings of Biometrics (ICB), 2013 International Conference on. Madrid: IEEE Biometric Council, 2013, pp. 1-8. ISBN 978-1-4799-0310-8. Available from: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6613025&refinements%3D4280507127%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A6612943%29
Publication language:english
Original title:The 2013 Speaker Recognition Evaluation in Mobile Environment
Title (cs):2013 Evaluace rozpoznávání mluvčího v mobilním prostředí
Pages:1-8
Proceedings:Proceedings of Biometrics (ICB), 2013 International Conference on
Conference:ICB-2013, The 6th IAPR International Conference on Biometrics
Place:Madrid, ES
Year:2013
URL:http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6613025&refinements%3D4280507127%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A6612943%29
ISBN:978-1-4799-0310-8
Publisher:IEEE Biometric Council
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2013/khouri_ibc2013_ICB13.pdf [PDF]
Keywords
speaker recognition, mobile environment, evaluation
Annotation
This paper presents the results of the participants to the evaluation on speaker verification in mobile environment.
Abstract
This paper evaluates the performance of the twelve primary systems submitted to the evaluation on speaker verification in the context of a mobile environment using the MOBIO database. The mobile environment provides a challenging and realistic test-bed for current state-of-the-art speaker verification techniques. Results in terms of equal error rate (EER), half total error rate (HTER) and detection error trade-off (DET) confirm that the best performing systems are based on total variability modeling, and are the fusion of several sub-systems. Nevertheless, the good old UBM-GMM based systems are still competitive. The results also show that the use of additional data for training as well as gender-dependent features can be helpful.
BibTeX:
@INPROCEEDINGS{
   author = {S. Elie Khoury and Bo{\v{s}}tjan Vesnicer and Javier
	Franco-Pedroso and Mireia S{\'{a}}nchez Diez and
	Tom{\'{a}}{\v{s}} Cipr and Petr Schwarz and David Leeuwen
	van and Dijana Petrovska-Delacretaz and Pavel Mat{\v{e}}jka
	and J. Luis Rodriguez-Fuentes and Gerard Chollet and
	Sebastien Marcel},
   title = {The 2013 Speaker Recognition Evaluation in Mobile
	Environment},
   pages = {1--8},
   booktitle = {Proceedings of Biometrics (ICB), 2013 International
	Conference on},
   year = {2013},
   location = {Madrid, ES},
   publisher = {IEEE Biometric Council},
   ISBN = {978-1-4799-0310-8},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=10529}
}

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