2023/01/17 by Pragma Kar, Shyamvanshikumar Singh, Kar, Pragma +7
Computer Science · Psychology · #Emotion and Mood Recognition #FOS: Computer and information sciences #Face recognition and analysis #Human-Computer Interaction (cs.HC) #Speech and Audio Processing
paper · pdf · doi:10.48550/arxiv.2301.06762
openalex publication_date 2023/01/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Facial expressions have been considered a metric reflecting a person's engagement with a task. While the evolution of expression detection methods is consequential, the foundation remains mostly on image processing techniques that suffer from occlusion, ambient light, and privacy concerns. In this paper, we propose ExpresSense, a lightweight application for standalone smartphones that relies on near-ultrasound acoustic signals for detecting users' facial expressions. ExpresSense has been tested on different users in lab-scaled and large-scale studies for both posed as well as natural expressions. By achieving a classification accuracy of ~75% over various basic expressions, we discuss the potential of a standalone smartphone to sense expressions through acoustic sensing.