  In-home IoT devices play a major role in healthcare systems as smart personal
assistants. They usually come with a voice-enabled feature to add an extra
level of usability and convenience to elderly, disabled people, and patients.
In this paper, we propose an efficient and privacy-preserving voice-based
search scheme to enhance the efficiency and the privacy of in-home healthcare
applications. We consider an application scenario where patients use the
devices to record and upload their voice to servers and the caregivers search
the interested voices of their patient's based on the voice content, mood, tone
and background sound. Our scheme preserves the richness and privacy of voice
data and enables accurate and efficient voice-based search, while in current
systems that use speech recognition the richness and privacy of voice data are
compromised. Specifically, our scheme achieves the privacy by employing a
homomorphic encryption; only encrypted voice data is uploaded to the server who
is unable to access the original voice data. In addition, our scheme enables
the server to selectively and accurately respond to caregiver's queries on the
voice data based on voice's feature similarity. We evaluate our scheme through
real experiments and show that our scheme even with privacy preservation can
successfully match similar voice data at an average accuracy of 80.8%.
