GSC-Based Binaural Speaker Separation Preserving Spatial Cues

Abstract

In this paper we investigate two methods for the preservation of spatial cues in binaural speaker separation. We develop these methods as extensions of our previously proposed model-based generalized sidelobe canceller (GSC) which utilizes a maximum likelihood technique for speaker localization. In the proposed implementation the adaptive GSC provides an estimate of the target signal as well as an estimation of target presence probability (TPP). Binaural outputs are generated in two different ways: In the first approach the binaural signals are rendered using the GSC output signal combined with the HRTF hypotheses which are adapted by the broadband localization. The second approach uses the GSC output and the TPP to determine a common spectral postfilter. We find that the adaptive beamformer combined with the binaural rendering technique leads to larger improvements of the quality of the desired signal and delivers less unnatural fluctuations as compared to the common spectral postfilter. Informal subjective tests as well as instrumental measurements in the presence of the listener head movements reveals, however, the benefit of the spatially motivated spectral postfilter for the preservation of binaural cues of both target and interferer signals.