Are disentangled representations all you need to build speaker anonymization systems?. (arXiv:2208.10497v1 [cs.SD])

Speech signals contain a lot of sensitive information, such as the speaker's
identity, which raises privacy concerns when speech data get collected. Speaker
anonymization aims to transform a speech signal to remove the source speaker's
identity while leaving the spoken content unchanged. Current methods perform
the transformation by relying on content/speaker disentanglement and voice
conversion. Usually, an acoustic model from an automatic speech recognition
system extracts the content representation while an x-vector system extracts
the speaker representation. Prior work has …

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