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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 21

Proceedings of the 2020 Federated Conference on Computer Science and Information Systems

Voice authentication based on the Russian-language dataset, MFCC method and the anomaly detection algorithm


DOI: http://dx.doi.org/10.15439/2020F43

Citation: Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 21, pages 537540 ()

Full text

Abstract. Almost all people's data is stored on their personal devices. For this reason, there is a need to protect information from unauthorized access by means of user authentication. PIN codes, passwords, tokens can be forgotten, lost, transferred, brute-force attacked. For this reason, biometric authentication is gaining in popularity. Biometric data are unchanged for a long time, different for users, and can be measured. This paper explores voice authentication due to the ease of use of this technology, since obtaining voice characteristics of users doesn't require an equipment in addition to the microphone, which is built into almost all devices. The method of voice authentication based on an anomaly detection algorithm has been proposed. The software module for text-independent authentication has been developed on the Python language. It's based on a new Mozilla's open source voice dataset``Common voice''. Experimental results confirmed the high accuracy of authentication by the proposed method.


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