Abstract
The scope of this paper is to check influence of the size of the speech corpus on the speaker recognition performance. Obtained results for TIMIT corpus are compared with results obtained for smaller database ROBOT. Additionally influence of feature dimensionality and size of the speaker model was tested. Achieved results show that the best results can be obtained for MFCC features. The lowest EER for larger TIMIT database are 4 times worse than the best result for ROBOT corpus which confirms that biometric systems should be tested on as large data sets as possible to assure that achieved error rates are statistically significant.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kłosowski, P.: Speech processing application based on phonetics and phonology of the polish language. In: Kwiecień, A., Gaj, P., Stera, P. (eds.) CN 2010. CCIS, vol. 79, pp. 236–244. Springer, Heidelberg (2010)
Dustor, A.: Voice verification based on nonlinear Ho-Kashyap classifier. In: International Conference on Computational Technologies in Electrical and Electronics Engineering SIBIRCON 2008, pp. 296–300. Novosibirsk (2008)
Dustor, A.: Speaker verification based on fuzzy classifier. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds.) Man-Machine Interactions. AISC, vol. 59, pp. 389–397. Springer, Heidelberg (2009)
Dustor, A., Kłosowski, P.: Biometric voice identification based on fuzzy kernel classifier. In: Kwiecień, A., Gaj, P., Stera, P. (eds.) CN 2013. CCIS, vol. 370, pp. 456–465. Springer, Heidelberg (2013)
Dustor, A., Kłosowski, P., Izydorczyk, J.: Influence of feature dimensionality and model complexity on speaker verification performance. In: Kwiecień, A., Gaj, P., Stera, P. (eds.) CN 2014. CCIS, vol. 431, pp. 177–186. Springer, Heidelberg (2014)
Dustor, A., Kłosowski, P., Izydorczyk, J.: Speaker recognition system with good generalization properties. In: International Conference on Multimedia Computing and Systems, ICMCS 2014, Marrakech, Morocco, April 2014, pp. 206–210. IEEE (2014)
Rabiner, L.R., Juang, B.H.: Fundamentals of Speech Recognition. Prentice Hall, NJ (1993)
Fazel, A., Chakrabartty, S.: An overview of statistical pattern recognition techniques for speaker verification. IEEE Circuits Syst. Mag. 11(2), 62–81 (2011)
TIMIT corpus. https://catalog.ldc.upenn.edu/LDC93S1
Adamczyk, B., Adamczyk, K., Trawiński, K.: Zasób mowy ROBOT. Biuletyn Instytutu Automatyki i Robotyki WAT 12, 179–192 (2000)
Linguistic data consortium. https://www.ldc.upenn.edu/
Acknowledgment
This work was supported by The National Centre for Research and Development (http://www.ncbir.gov.pl) under Grant number POIG.01.03.01-24-107/12 (Innovative speaker recognition methodology for communications network safety).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Dustor, A., Kłosowski, P., Izydorczyk, J., Kopański, R. (2015). Influence of Corpus Size on Speaker Verification. In: Gaj, P., Kwiecień, A., Stera, P. (eds) Computer Networks. CN 2015. Communications in Computer and Information Science, vol 522. Springer, Cham. https://doi.org/10.1007/978-3-319-19419-6_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-19419-6_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19418-9
Online ISBN: 978-3-319-19419-6
eBook Packages: Computer ScienceComputer Science (R0)