Revisiting Speech Content Privacy
Abstract
In this paper, we discuss an important aspect of speech privacy: protecting spoken content. New capabilities from the field of machine learning provide a unique and timely opportunity to revisit speech content protection. There are many different applications of content privacy, even though this area has been under-explored in speech technology research. This paper presents several scenarios that indicate a need for speech content privacy even as the specific techniques to achieve content privacy may necessarily vary. Our discussion includes several different types of content privacy including recoverable and non-recoverable content. Finally, we introduce evaluation strategies as well as describe some of the difficulties that may be encountered.
Cite
@article{arxiv.2110.06760,
title = {Revisiting Speech Content Privacy},
author = {Jennifer Williams and Junichi Yamagishi and Paul-Gauthier Noe and Cassia Valentini Botinhao and Jean-Francois Bonastre},
journal= {arXiv preprint arXiv:2110.06760},
year = {2021}
}
Comments
Accepted to ISCA Security and Privacy in Speech Communication (1st SPSC Symposium)