Towards End-to-End Private Automatic Speaker Recognition. (arXiv:2206.11750v1 [eess.AS])

The development of privacy-preserving automatic speaker verification systems
has been the focus of a number of studies with the intent of allowing users to
authenticate themselves without risking the privacy of their voice. However,
current privacy-preserving methods assume that the template voice
representations (or speaker embeddings) used for authentication are extracted
locally by the user. This poses two important issues: first, knowledge of the
speaker embedding extraction model may create security and robustness
liabilities for the authentication system, as this …

end end-to-end recognition