Multi-channel speaker localization and separation using a model-based GSC and an inertial measurement unit

In this paper we propose a novel multi-channel algorithm to separate simultaneous speakers in an environment where the microphone array is subject to movement. When the microphones are mounted to a person's head, for instance, the movements can lead to ambiguities with respect to the sources and to distortions in the processed signal. The proposed system estimates the direction-of-arrival of the speaker's signals relative to the array and updates these estimates using an inertial measurement unit (IMU). A GMM-based localization model is used to compute the posterior probabilities of source activity in each time-frequency bin and its parameters are re-estimated during array movements. Then, a model-based generalized side-lobe canceler (GSC) whose components are continuously updated, is employed for the separation of sources. For various speeds of microphone array rotation, it is demonstrated that the IMU-based system delivers improved speech quality when compared to the baseline technique without IMU.