Speaker anonymization aims to suppress speaker individuality to protect
privacy in speech while preserving the other aspects, such as speech content.
One effective solution for anonymization is to modify the McAdams coefficient.
In this work, we propose a method to improve the security for speaker
anonymization based on the McAdams coefficient by using a speech watermarking
approach. The proposed method consists of two main processes: one for embedding
and one for detection. In embedding process, two different McAdams coefficients
represent binary bits “0″ and “1″. The watermarked speech is then obtained by
frame-by-frame bit inverse switching. Subsequently, the detection process is
carried out by a power spectrum comparison. We conducted objective evaluations
with reference to the VoicePrivacy 2020 Challenge (VP2020) and of the speech
watermarking with reference to the Information Hiding Challenge (IHC) and found
that our method could satisfy the blind detection, inaudibility, and robustness
requirements in watermarking. It also significantly improved the anonymization
performance in comparison to the secondary baseline system in VP2020.

By admin