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Privacy-Preserving Speaker Authentication

  • Manas Pathak
  • Jose Portelo
  • Bhiksha Raj
  • Isabel Trancoso
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7483)

Abstract

Speaker authentication systems require access to the voice of the user. A person’s voice carries information about their gender, nationality 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 simultaneously 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.

Keywords

Speaker Recognition Privacy Preserve Homomorphic Encryption Universal Background Model Target Speaker 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Manas Pathak
    • 1
  • Jose Portelo
    • 2
  • Bhiksha Raj
    • 1
  • Isabel Trancoso
    • 2
  1. 1.Carnegie Mellon UniversityPittsburghUSA
  2. 2.INESC-ID/ISTLisbonPortugal

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