DOA Estimation of Audio Sources in Reverberant Environments

Reverberation is well-known to have a detrimental impact on many localization methods for audio sources. We address this problem by imposing a model for the early reflections as well as a model for the audio source itself. Using these models, we propose two iterative localization methods that estimate the direction-of-arrival (DOA) of both the direct path of the audio source and the early reflections. In these methods, the contribution of the early reflections is essentially subtracted from the signal observations before localization of the direct path component, which may reduce the estimation bias. Our simulation results show that we can estimate the DOA of the desired signal more accurately with this procedure compared to state-of-the-art estimator in both synthetic and real data experiments with reverberation.Accepted Author ManuscriptCircuits and System

On the Impact of Quantization on Binaural MVDR Beamforming

Multi-microphone noise reduction algorithms in binaural hearing aids which cooperate through a wireless link have the potential to become of great importance in future hearing aid systems. However, limited transmission capacity of such devices necessitates the data compression of signals transmitted from one hearing aid to the contralateral one. In this paper we study the impact of quantization as a data compression scheme on the performance of the multi-microphone noise reduction algorithms. Using the binaural minimum variance distortionless response (BMVDR) beamformer as an illustration, we propose a quantization aware beamforming scheme which uses a modified cross power spectral density (CPSD) of the system noise including the quantization noise (QN). Moreover, several assumptions on the QN are investigated in the proposed method. Based on the output SNR, we compare different variations of the proposed method with the conventional BMVDR beamformer. The results confirm the improved performance of the proposed method.Circuits and System