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Method for automatic on-line updating of personal biometric data based on speech signal of the biometric system user

https://doi.org/10.32446/0368-1025it.2021-11-60-66

Abstract

The problem of “aging” of personal biometric data over time is considered. A method is proposed to overcome it by automatically updating the personal biometric data by using the speech signals of registered users obtained during latest requests for their identification and online service. The proposed method uses a scale-invariant indicator of the voice template quality. As a consequence, it is characterized by guaranteed reliability of the decisions made in the conditions of a wide speech signal dynamic range. It is shown that a guaranteed level of significance of decisions made by an observer is provided. The proposed method is implemented in a special software, which was used to experimentally estimate its effectiveness with real speech data. The obtained results are intended for use in the development of new and modernization of existing software and technologies for the personal biometric data automated quality control and updating.

About the Authors

A. V. Savchenko
National Research University Higher School of Economics
Russian Federation

Andrey V. Savchenko

Nizhniy Novgorod



V. V. Savchenko
Nizhny Novgorod State Linguistic University
Russian Federation

Vladimir V. Savchenko

Nizhniy Novgorod



References

1. Chawla S. K., Lamba V., Jangra S., International Journal of Innovative Technology and Exploring Engineering, 2019, vol. 9, no. 11,pp. 2278–3075. https://doi.org/10.35940/ijitee.A4756.119119

2. Manjani I. et al., IEEE 8th International Conference on Biometrics Theory, Applications and Systems, 2016. https://doi.org/10.1109/BTAS.2016.7791202

3. Savchenko V. V., Savchenko A. V., Measurement Techniques, 2019, vol. 62, no. 12, pp. 1071–1078. https://doi.org/10.1007/s11018-020-01736-w

4. Savchenko V. V., Savchenko А. V., Measurement Techniques, 2020, vol. 63, no. 5, pp. 391–400. https://doi.org/10.1007/s11018-020-01800-5

5. Smallman M., Biometric Technology Today, 2017, vol. 2017, no. 1, pp. 5–7. htt ps://doi.org/10.1016/S0969-4765(17)30013-9

6. Crosswhite N. et al., Image and Vision Computing, 2018, vol. 79, pp. 35–48. https://doi.org/10.1016/j.imavis.2018.09.002

7. Orrù G., Marcialis G. L., Roli F., Pattern Recognition, 2020, vol. 100, 107121. https://doi.org/10.1016/j.patcog.2019.107121

8. Singh M., Singh R., Ross A., Information Fusion, 2019, vol. 52, no. 12, pp. 187–205. https://doi.org/10.1016/j.inffus.2018.12.003

9. Lebedeva N. N., Karimova E. D., Akusticheskie kharakteristiki rechevogo signala kak pokazatel’ funktsional’nogo sostoyaniya cheloveka, Uspekhi fi ziologicheskikh nauk, 2014, vol. 45, no. 1, рр. 57–95. (In Russ.)

10. Savchenko V. V., Savchenko A. V., Measurement Techniques, 2021, vol. 63, no. 11, pp. 917–925. https://doi.org/10.1007/s11018-021-01864-x

11. Savchenko A. V., Savchenko V. V., Savchenko L. V., Mathematical Optimizat ion Theory and Operations Research MOTOR 2020, Lecture Notes in Computer Science, Springer, Cham, 2020, 12095. https://doi.org/10.1007/978-3-030-49988-4_30

12. Kullback S., Information Theory and Statistics, New York, Dover Publications, 1997, 432 p.

13. Savchenko V. V., Journal of Communications Technology and Electronics, 2019, vol. 64, no. 6, pp. 590–596. https://doi.org/10.1134/S1064226919060093

14. Savchenko V. V., Savchenko L. V., Measurement Techniques, 2019, vol. 62, no. 9, рр. 832–839. https://doi.org/10.1007/s11018-019-01702-1

15. Savchenko V. V., Savchenko A. V., Journal of Communications Technology and Electronics, 2020, vol. 65, no. 11, pp. 1311– 1317. https://doi.org/10.1134/S1064226920110157

16. Kashani H. B., Sayadiyan A., Sheikhzadeh H., Speech Communication, 2017,vol. 91, pp. 28–48. https://doi.org/10.1016/j.specom.2017.04.008

17. Savchenko A. V., PeerJ Computer Science, 2019, 5e:197. https://doi.org/10.7717/peerj-cs.197

18. Borovkov A. A. Matematicheskaya statistika. St. Peterburg, Publ., 2010, 704 p. (In Russ.)

19. Meng Zh., Umair Bin Altaf M., Juang B.-H., Digital Signal Processing, 2020, v ol. 101, 102672. https://doi.org/10.1016/j.dsp.2020.102672

20. Marple S. L., Digital Spectral Analysis with Applications, 2nd ed., Mineola, New York, Dover Publications, 2019, 432 p. https:// www.goodreads.com/book/show/19484239

21. Muller P. H., Neumann P., Storm R., Tafeln der mathematischen statistik, Leipzig, VEB Fachbuchverlag, 1973, 279 р. https://doi.org/10.1002/bimj.19740160816


Review

For citations:


Savchenko A.V., Savchenko V.V. Method for automatic on-line updating of personal biometric data based on speech signal of the biometric system user. Izmeritel`naya Tekhnika. 2021;(11):60-66. (In Russ.) https://doi.org/10.32446/0368-1025it.2021-11-60-66

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ISSN 0368-1025 (Print)
ISSN 2949-5237 (Online)