Acoustic Beamformers and Their Applications in Hearing Aids

Abstract

This work introduces new binaural beamforming algorithms for hearing aids, with a robustness to errors in the estimate of the target speaker direction of arrival (DOA) and a good trade-off between noise reduction and preservation of the noise/interferers spatial impression. Three robust designs are proposed, and their robustness is confirmed by simulation results. These robust designs are a combination of binaural and monaural beamformers using two different microphone configurations: one for low frequency components and one for high frequency components. The robust designs are also found to be robust to mismatch between the anechoic propagation models used for the beamformers designs and the reverberant propagation models used to generate the signals at the microphones in the simulations. To preserve the binaural cues of the noise/interferers in the binaural beamformer outputs, a method based on a mixing/selection of different available binaural signals is proposed, using a classification from the phase and magnitude of a complex coherence function. This method is added as a post processor to the beamforming designs robust to target DOA mismatch. Simulation results show that the resulting mixed binaural output signals have a good binaural cues preservation level that outperform the benchmark design, with significant noise reduction and low target distortion. Since knowledge of source DOAs is important for beamforming noise reduction, a beamformer-based broadband multi-source DOA detection system is also developed in the thesis, using information from different frequencies or sub‐bands to obtain global estimates of sources DOAs. Simulation results shows that using one beamformer on each side is capable of detecting the DOAs of active sources under several acoustic scenarios, including scenarios with one, two, or three sources, and with or without the presence of some level of diffuse noise.