MagSound

Abstract

Wireless earphones are pervasive acoustic sensing platforms that can be used for many applications such as motion tracking and handwriting input. However, wireless earphones suffer clock offset between the connected smart devices, which would accumulate error rapidly over time. Moreover, compared with smartphone and voice assistants, the acoustic signal transmitted by wireless earphone is much weaker due to the poor frequency response. In this paper, we propose MagSound, which uses the built-in magnets to improve the tracking and acoustic sensing performance of Commercial-Off-The-Shelf (COTS) earphones. Leveraging magnetic field strength, MagSound can predict the position of wireless earphones free from clock offset, which can be used to re-calibrate the acoustic tracking. Further, the fusion of the two modalities mitigates the accumulated clock offset and multipath effect. Besides, to increase the robustness to noise, MagSound employs finely designed Orthogonal Frequency-Division Multiplexing (OFDM) ranging signals. We implement a prototype of MagSound on COTS and perform experiments for tracking and handwriting input. Results demonstrate that MagSound maintains millimeter-level error in 2D tracking, and improves the handwriting recognition accuracy by 49.81%. We believe that MagSound can contribute to practical applications of wireless earphones-based sensing.