2024/04/27 by Bhawana Chhaglani, Chhaglani, Bhawana, Jeremy Gummeson +3 · 2 citations
Computer Science · #Audio and Speech Processing (eess.AS) #Digital Media Forensic Detection #FOS: Computer and information sciences #FOS: Electrical engineering #Music and Audio Processing #Sound (cs.SD) #Speech and Audio Processing #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2404.18002
openalex publication_date 2024/04/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Audio signals can reveal intimate details about a person's life, including their conversations, health status, emotions, location, and personal preferences. Unauthorized access or misuse of this information can have profound personal and social implications. In an era increasingly populated by devices capable of audio recording, safeguarding user privacy is a critical obligation. This work studies the ethical and privacy concerns in current audio classification systems. We discuss the challenges and research directions in designing privacy-preserving audio sensing systems. We propose privacy-preserving audio features that can be used to classify wide range of audio classes, while being privacy preserving.