SPECOM 2013: Speech and Computer pp 345-353 | Cite as
The Problem of Voice Template Aging in Speaker Recognition Systems
Abstract
It is well known that device, language and environmental mismatch adversely affect speaker recognition performance. Much less attention is paid to effect of age-related voice changes on speaker recognition performance. In this paper we attempted to answer if speaker recognition algorithms have the re-sistance to age-related changes, and how often we have to update the voice bi-ometric templates. We have investigated such effects basing on the speech da-tabase collected during the period 2006-2010 and have found a clear trend of degradation of the performance of automatic speaker recognition systems in a time interval of up to 4 years.
Keywords
template aging template update rate speaker recognitionPreview
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References
- 1.Schötz, S., Müller, C.: A Study of Acoustic Correlates of Speaker Age. In: Müller, C. (ed.) Speaker Classifcation II. LNCS (LNAI), vol. 4441, pp. 1–9. Springer, Heidelberg (2007)CrossRefGoogle Scholar
- 2.Beigi, H.: Effects of time lapse on speaker recognition results. In: Proc. 16th Int. Conf. on Digital Signal Processing (DSP 2009), pp. 1260–1265. IEEE Press, Piscataway (2009)Google Scholar
- 3.Czajka, A.: Call for cooperation: biometric template ageing. In: Proc. of IBPC 2010, NIST (2010)Google Scholar
- 4.Linville, S.E.: Vocal Aging. Singular Publishing Group, San Diego (2001)Google Scholar
- 5.Mishra, A.: Multimodal Biometrics it is: Need for Future Systems. International Journal of Computer Applications 3(4), 28–33 (2010)CrossRefGoogle Scholar
- 6.Carls, J.W.: A framework for analyzing biometric template aging and renewal prediction. Ph.D. Thesis, Air Force Institute of Technology (2009)Google Scholar
- 7.Ajmera, J., Burkhardt, F.: Age and gender classification using modulation cepstrum. In: Proc. Speaker Odyssey (2008)Google Scholar
- 8.Metze, F., Ajmera, J., Englert, R., Bub, U., Burkhardt, F., Stegmann, J., Müller, C., Huber, R., Andrassy, B., Bauer, J., Littel, B.: Comparison of four approaches to age and gender recognition for telephone applications. In: Proc. ICASSP, vol. 4, pp. 1089–1092 (2007)Google Scholar
- 9.Muller, C., Burkhardt, F.: Combining short-term cepstral and long-term prosodic features for automatic recognition of speaker age. In: Proc. of Interspeech (2007)Google Scholar
- 10.Simonchik, K.: Identification system of the speaker’s age group by spontaneous record. Scientific and Technical Journal of Information Technologies, Mechanics and Optics 82(6), 89–93 (2012)Google Scholar
- 11.Wolters, M., Vipperla, R., Renals, S.: Age Recognition for Spoken Dialogue Systems: Do We Need It? In: Proc. of Interspeech, pp. 1435–1438 (2009)Google Scholar
- 12.Przybocki, M.A., Martin, A.F., Le, A.N.: NIST speaker recognition evaluations utilizing the mixer corpora - 2004, 2005, 2006. IEEE Trans. Audio Speech Lang. Process. 15(7), 1951–1959 (2007)CrossRefGoogle Scholar
- 13.Kohler, T.: The 2010 NIST Speaker Recognition Evaluation. IEEE Speech and Language Processing Technical Committee’s Newsletter, SLTC Newsletter (2010)Google Scholar
- 14.Kelly, F., Drygajlo, A., Harte, N.: Speaker Verification with Long-Term Ageing Data. In: International Biometric Conference (2012)Google Scholar
- 15.Campbell, J.P., Shen, W., Campbell, W.M., Schwartz, R., Bonastre, J.-F., Matrouf, D.: Forensic speaker recognition. IEEE Signal Processing Magazine 26(2), 95–103 (2009)CrossRefGoogle Scholar
- 16.STC Ltd., The database for speaker identification RUASTEN, registration certificate – 2010620533, RU (2010)Google Scholar
- 17.Labutin, P., Koval, S., Raev, A.: Speaker identification based on the statistical analysis of f0. In: Proc. IAFPA, Plymouth, UK (2007)Google Scholar
- 18.Labutin, P., Koval, S., Raev, A., Smirnova, N., Stolbov, M., Tampel, I., Khitrov, M.: Speaker recognition system for standard telephone network. In: Proc. SPECOM 2005, Patras, Greece, pp. 563–566 (2005)Google Scholar
- 19.Matveev, Y.N., Simonchik, K.K.: The speaker identification system for the NIST SRE 2010. In: GraphiCon 2010, St. Petersburg, Russia, pp. 315–319 (2010)Google Scholar
- 20.Furui, S.: Comparison of speaker recognition methods using statistical features and dynamic features. IEEE Transactions on Acoustics, Speech and Signal Processing 29(3), 342–350 (1981)CrossRefGoogle Scholar