SonicFER: Facial Expressions Tracking Through a Commercial Smartphone Speaker

Facial expression recognition technology plays a significant role in advancing the intelligence and personalization of human-computer interaction. Although ultrasonic-based expression recognition methods already exist, most rely on phase shifts or Doppler effects, which suffer from insufficient resolution to accurately capture subtle facial expression variations. To address this issue, this paper proposes an innovative facial expression recognition system, SonicFER, which utilizes smartphones to emit ultrasonic waves and receive echoes, achieving fine-grained perception of facial expressions through real-time monitoring and analysis of channel impulse response (CIR). To effectively detect facial expression movements while eliminating static interference and minor motion artifacts, this paper employs a differential operation combined with variance calculation, along with setting appropriate thresholds for filtering. Through rigorous experimental evaluation, SonicFER achieves a high accuracy of 91.2% in recognizing six common facial expressions and outperforms state-of-the-art technologies across various real-world scenarios.