Analysis of dual-channel ICA-based blocking matrix for improved noise estimation

Abstract

For speech enhancement or blind signal extraction (BSE), estimating interference and noise characteristics is decisive for its performance. For multichannel approaches using multiple microphone signals, a BSE scheme combining a blocking matrix (BM) and spectral enhancement filters was proposed in numerous publications. For such schemes, the BM provides a noise estimate by suppressing the target signal only. The estimated noise reference is then used to design spectral enhancement filters for the purpose of noise reduction. For designing the BM, 'Directional Blind Source Separation (BSS)' was already proposed earlier. This method combines a generic BSS algorithm with a geometric constraint derived from prior information on the target source position to obtain an estimate for all interfering point sources and diffuse background noise. In this paper, we provide a theoretical analysis to show that Directional BSS converges to a relative transfer function (RTF)-based BM. The behavior of this informed signal separation scheme is analyzed and the blocking performance of Directional BSS under various acoustical conditions is evaluated. The robustness of Directional BSS regarding the localization error for the target source position is verified by experiments. Finally, a BSE scheme combining Directional BSS and Wiener-type spectral enhancement filters is described and evaluated.

Multichannel Signal Enhancement Algorithms for Assisted Listening Devices: Exploiting spatial diversity using multiple microphones

“…6 depicts the overall transfer function W H H from a given source position in a reverberant environment for a null-steering (delay-and-subtract) beamformer and one output channel of an ICA system, thereby demonstrating the actual interference suppression performance in a reverberant environment [40]. The improved spatial null achieved by ICA confirms the hypothesis that, due to capturing all correlated components belonging to the same source in the same output, ICA does not only suppress the direct path but also reflections of an interfering source, e.g., [40]. Nevertheless, one has to bear in mind that the suppression of reflections results from a compromise in the spatial directivity, which a null-steering beamformer cannot offer.…”

“…More recently, a constrained BSS scheme has been proposed to identify the filters of two-channel blocking matrices [40], which does not need source activity information and continuously delivers up-to-date estimates for noise and interference. For this, the cost function in (23) is complemented by a quadratic constraint for one output (here y p ) steering a null towards the target source:…”

Pseudo-Determined Blind Source Separation for Ad-hoc Microphone Networks

“…The permutation alignment result of the regular DBSS is crucial to the reference-based scheme and could be improved with two strategies: exploiting the information from more sensors, as done by some OBSS algorithms [12], [29]; or considering a time-domain DBSS algorithm, which usually has worse separation performance but is free from permutation ambiguities [45]. Finally, the noise PSD estimation in the postfiltering block employs a simple averaging scheme: exploiting the demixing filter coefficients could further improve the noise PSD estimation performance [38], [46].…”

Relative transfer function (RTF) estimation utilising peaks in time‐domain RTF

“…To avoid such reliance on the additional detectors, independent component analysis-based blind source separation (BSS) algorithms to realise BM were proposed [3]. More recently, directional BSS which introduced geometric constraint to BSS was considered in realising BM [4] and its effectiveness was shown with respect to the blocking performance of BM. Moreover, this algorithm can be applied to underdetermined scenarios so that it can deal with practical situations, i.e.…”

“…This holds only when the BSS system suppresses only s 1 in y 1 which cannot be guaranteed if the number of the sound sources exceeds the number of the sensors. In [4], a geometric constraint has been proposed to satisfy the condition. This constraint was used to force BSS weights that correspond to output y 1 to have a spatial null towards the direction of the target source.…”