Cepstral voices verification#

Identification features should include emotional state and cepstral characteristics of voice. In this paper, we provide the analysis of existing speech synthesis technologies and the most promising attacks detection methods for banking and financial organizations. ASV security remains an unsolved problem, because there is no universal solution that does not depend on the speech synthesis methods used by the attacker. Anti-spoofing approaches can be based on searching for phase and tone frequency anomalies appearing during speech synthesis and on a preliminary knowledge of the acoustic differences of specific speech synthesizers. Speech synthesis attacks are the most dangerous as the technologies of speech synthesis are developing rapidly (GAN, Unit selection, RNN, etc.).

Cepstral voices verification#

Automatic speaker verification systems (ASV) are vulnerable to various types of spoofing attacks: impersonation, replay attacks, voice conversion, and speech synthesis attacks. Voice biometrics security is a large-scale problem significantly raised over the past few years. The paper considers methods of countering speech synthesis attacks on voice biometric systems in banking. Vorobeva6^ДЎ'2'3'4'5'6 ITMO University, Saint Petersburg, 197101, Russian Federation 4 Laboratory PPS Ltd, Saint Petersburg, 199178, Russian Abstract Methods of countering speech synthesis attacks on voice biometric systemsДЄleksandr Yu. SCIENTIFIC AND TECHNICAL JOURNAL OF INFORMATION TECHNOLOGIES, MECHANICS AND OPTICS January-February 2021 Vol. The proposed approach could be used for design and development of authentication systems for banking and п¬Ѓnancial organizations resistant to speech synthesis attacks.

Dynamic passwords database should contain words that are difп¬Ѓcult to synthesize and pronounce. Analysis of speech intelligibility and semantics are also important. Analyzed signal should not be too smooth and containing unnatural noises or sharp interruptions changes in the signal level. It is necessary to adjust the userвЂ™s voiceprint regularly. Identiп¬Ѓcation features should include emotional state and cepstral characteristics of voice. In this paper, we provide the analysis of existing speech synthesis technologies and the most promising attacks detection methods for banking and п¬Ѓnancial organizations. Anti-spooп¬Ѓng approaches can be based on searching for phase and tone frequency anomalies appearing during speech synthesis and on a preliminary knowledge of the acoustic differences of speciп¬Ѓc speech synthesizers. Automatic speaker veriп¬Ѓcation systems (ASV) are vulnerable to various types of spooп¬Ѓng attacks: impersonation, replay attacks, voice conversion, and speech synthesis attacks.

Voice biometrics security is a large-scale problem signiп¬Ѓcantly raised over the past few years.