Privacy‐preserving speaker verification system based on binary I‐vectors
Résumé
Speaker verification is a key technology in many services and applications like smartphones
and intelligent digital assistants. These applications usually require users to transmit their
recordings, features, or models from their voices over untrusted public networks which
stored and processed them on cloud‐based infrastructure. Furthermore, the voice signal
contains a great deal of the speaker's personal and private information which raises several
privacy issues. Therefore, it is necessary to develop speaker verification systemsthat protect
the user's voice against such threats. Herein, the cancellable biometric systems have been
introduced as a privacy‐preserving solution. A cancellable method for speaker verification
systemsis proposed using speakeri‐vector embeddings.This method includestwo stages: (i)
i‐vector binarisation and (ii) the protection of the binary i‐vector with a shuffling scheme
derived from a user‐specific key. Privacy evaluation of this method according to the standards of biometric information protection (ISO/IEC 24745) shows that the proposed
cancellable speaker verification system achieves the revocability, unlinkability, and irreversibility requirements. Moreover, the cancellable system improves biometric performance
compared with the unprotected system and makes it resistant to different attack scenarios.
Additionally, we demonstrate that this method can also operate to protect deep neural
network speaker embeddings such as x‐vectors.