Privacy-preserving speaker authentication

Abstract. Speaker authentication systems require access to the voice of the user. A person’s voice carries information about their gender, na-tionality etc., all of which become accessible to the system, which could abuse this knowledge. The system also stores users ’ voice prints – these may be stolen and used to impersonate the users elsewhere. It is therefore important to develop privacy preserving voice authentication techniques that enable a system to authenticate users by their voice, while simulta-neously obscuring the user’s voice and voice patterns from the system. Prior work in this area has employed expensive cryptographic tools, or has cast authentication as a problem of exact match with compromised accuracy. In this paper we present a new technique that employs secure binary embeddings of feature vectors, to perform voice authentication in a privacy preserving manner with minimal computational overhead and little loss of classification accuracy.