Detecting In-Person Conversations in Noisy Real-World Environments with Smartwatch Audio and Motion Sensing

ArXi:2507.12002v2 Announce Type: replace Social interactions play a crucial role in shaping human behavior, relationships, and societies. It encompasses various forms of communication, such as verbal conversation, non-verbal gestures, facial expressions, and body language. In this work, we develop a novel computational approach to detect face-to-face verbal conversations, a foundational aspect of human social interactions. We leverage multimodal data captured by a commodity smartwatch, specifically synchronizing microaudio with 6-axis inertial signals (accelerometer and gyroscope.