Obfuscation via pitch-shifting for balancing privacy and diagnostic utility in voice-based cognitive assessment.

ABSTRACT:

Introduction

Digital voice analysis is gaining traction as a tool to differentiate cognitively normal from impaired individuals. However, voice data poses privacy risks due to the potential identification of speakers by automated systems.

Methods

We developed a framework that uses weighted linear interpolation of privacy and utility metrics to balance speaker obfuscation and cognitive integrity in cognitive assessments. This framework applies pitch-shifting for speaker obfuscation while preserving cognitive speech features. We tested it on digital voice recordings from the Framingham Heart Study (N=128) and Dementia Bank Delaware corpus (N=85), both containing responses to neuropsychological tests.

Results

The tool effectively obfuscated speaker identity while maintai

SUBMITTER: Ahangaran M 

PROVIDER: S-EPMC11623733 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature