Voice interfaces are increasingly used in high stakes domains such as mobile banking, smart home security, and hands free healthcare. Meanwhile, modern generative models have made high quality voice forgeries inexpensive and easy to create, eroding confidence in voice authentication alone. To strengthen protection against such attacks, we present a second authentication factor that combines acoustic evidence with the unique motion patterns of a speaker's lower face. By placing lightweight inertial sensors around the mouth to capture mouth opening and evolving lower facial geometry, our system records a distinct motion signature with strong discriminative power across individuals. We built a prototype and recruited 43 participants to evaluate the system under four conditions seated, walking on level ground, walking on stairs, and speaking with different language backgrounds (native vs. non native English). Across all scenarios, our approach consistently achieved a median equal error rate (EER) of 0.01 or lower, indicating that mouth movement data remain robust under variations in gait, posture, and spoken language. We discuss specific use cases where this second line of defense could provide tangible security benefits to voice authentication systems.

翻译：暂无翻译