Speech processing systems require complete access to the speech signal. Yet, speech is often considered the most private of human communication. Thus, subjects who may otherwise be willing to use a voice-processing system may consider it unacceptable that their voices may be recorded and listened to by third parties in the process.
The problem extends beyond mere unwillingness of active users to expose their speech. Call centers and voice data warehouses possess large quantities of voice recordings that might be mined for useful information; however they cannot do so as that would violate the privacy of the users whose voices are stored. Similarly, security agencies who wish to monitor conversations etc. to perform the vital act of securing citizens from potential terrorist or other malicious activity will necessarily also end up invading the privacy of innocent citizens whose conversations they overhear.
In this research we are developing secure and private mechanisms that will allow voice to be processed without exposing its contents. Using these methods a user may, for example, contribute voice recordings to mining or learning system secure in teh knowledge that nobody including snoopers or the receipient of his data will actually be able discern any useful information from what they obtain besides what the users themselves are willing to reveal.