MIMO noise suppression preserving spatial cues for sound source localization in mobile robot

Abstract

In this paper, a multi-input multi-output (MIMO) noise suppression (NS) algorithm for sound source localization (SSL) is proposed in mobile robot environment. Especially for the mobile robot, some ego noise (e.g., motor noise) is naturally generated and it becomes a dominant signal at microphone array, which seriously damages the performance of the SSL. Therefore, the proposed MIMO NS algorithm is designed not only to suppress the noise but also to preserve spatial information of sound sources. To this end, the recent MIMO time-domain audio separation network (TasNet) with preserving spatial cues for binaural source separation is extended to tetrahedral microphone array in the proposed MIMO NS algorithm. Furthermore, weighted phase error (WPE) between inter-channels is additionally employed in the loss function, which can improve the performance especially in preserving inter-channel time difference (ITD). The performance of the proposed approach is verified within the context of the robot vacuum cleaner, which shows from simulations and real experiments that the proposed approach can preserve the spatial information as well as remove the vacuum noise.