Sound Localization and Separation in Three-dimensional Space Using a Single Microphone with a Metamaterial Enclosure

Abstract: Conventional approaches to sound localization and separation are based on microphone arrays in artificial systems. Inspired by the selective perception of human auditory system, we design a multi-source listening system which can separate simultaneous overlapping sounds and localize the sound sources in three-dimensional space, using only a single microphone with a metamaterial enclosure. The enclosure modifies the frequency response of the microphone in a direction-dependent way by giving each direction a signature. Thus, the information about the location and audio content of sound sources can be experimentally reconstructed from the modulated mixed signals using compressive sensing algorithm. Owing to the low computational complexity of the proposed reconstruction algorithm, the designed system can also be applied in source identification and tracking. The effectiveness of the system in multiple real scenarios has been proved through multiple random listening tests. The proposed metamaterial-based single-sensor listening system opens a new way of sound localization and separation, which can be applied to intelligent scene monitoring and robot audition.