Differentially Private Speaker Anonymization. (arXiv:2202.11823v2 [cs.SD] UPDATED)

Sharing real-world speech utterances is key to the training and deployment of
voice-based services. However, it also raises privacy risks as speech contains
a wealth of personal data. Speaker anonymization aims to remove speaker
information from a speech utterance while leaving its linguistic and prosodic
attributes intact. State-of-the-art techniques operate by disentangling the
speaker information (represented via a speaker embedding) from these attributes
and re-synthesizing speech based on the speaker embedding of another speaker.
Prior research in the privacy community …

anonymization arxiv