Title :
Theoretical Analysis of Binaural Multimicrophone Noise Reduction Techniques
Author :
Cornelis, Bram ; Doclo, Simon ; Van Dan Bogaert, Tim ; Moonen, Marc ; Wouters, Jan
Author_Institution :
Dept. of Electr. Eng., Katholieke Univ. Leuven, Leuven, Belgium
Abstract :
Binaural hearing aids use microphone signals from both left and right hearing aid to generate an output signal for each ear. The microphone signals can be processed by a procedure based on speech distortion weighted multichannel Wiener filtering (SDW-MWF) to achieve significant noise reduction in a speech + noise scenario. In binaural procedures, it is also desirable to preserve binaural cues, in particular the interaural time difference (ITD) and interaural level difference (ILD), which are used to localize sounds. It has been shown in previous work that the binaural SDW-MWF procedure only preserves these binaural cues for the desired speech source, but distorts the noise binaural cues. Two extensions of the binaural SDW-MWF have therefore been proposed to improve the binaural cue preservation, namely the MWF with partial noise estimation (MWF-eta) and MWF with interaural transfer function extension (MWF-ITF). In this paper, the binaural cue preservation of these extensions is analyzed theoretically and tested based on objective performance measures. Both extensions are able to preserve binaural cues for the speech and noise sources, while still achieving significant noise reduction performance.
Keywords :
Wiener filters; acoustic noise; acoustic signal processing; hearing; hearing aids; microphones; noise abatement; binaural cue preservation; binaural hearing aids; binaural multimicrophone noise reduction techniques; interaural level difference; interaural time difference; interaural transfer function extension; microphone signals; partial noise estimation; speech distortion weighted multichannel Wiener filtering; Binaural cues; binaural hearing aid; localization; multichannel Wiener filtering; noise reduction;
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
DOI :
10.1109/TASL.2009.2028374