Robustness of spatial average equalization: A statistical reverberation model approach

Abstract

Traditionally, multiple listener room equalization is performed to improve sound quality at all listeners, during audio playback, in a multiple listener environment (e.g., movie theaters, automobiles, etc.). A typical way of doing multiple listener equalization is through spatial averaging, where the room responses are averaged spatially between positions and an inverse equalization filter is found from the spatially averaged result. However, the equalization performance, will be affected if there is a mismatch between the position of the microphones (which are used for measuring the room responses for designing the equalization filter) and the actual center of listener head position (during playback). In this paper, we will present results on the effects of microphone-listener mismatch on spatial average equalization performance. The results indicate that, for the analyzed rectangular configuration, the region of effective equalization depends on (i) the distance of a listener from the source, (ii) the amount of mismatch between the responses, and (iii) the frequency of the audio signal. We also present some convergence analysis to interpret the results.

Equalization of Multichannel Acoustic Systems in Oversampled Subbands

“…The advantages of this filter-bank include straightforward implementation of fractional oversampling and computationally efficient implementations [29]. Within the framework of the GDFT filter-bank, the analysis filters, , are calculated from a single prototype filter, , with bandwidth according to the relation [29] ( 15) where the properties of the frequency and time offset terms, and , are discussed in, for example, [29]. We set these to and as in [31].…”

“…Bharitkar et al [15] use spatially averaged RTFs for the design of the equalization filter. In [16], the authors modify the desired signal in the multichannel inverse filter design, such that the late reverberation is equalized while the early reflections are preserved.…”

Subband Method for Multichannel Least Squares Equalization of Room Transfer Functions

“…However, it has been observed that exact equalization is of limited value in practice, when the RTF estimates contains even moderate errors [1,3,9]. Various alternatives have been proposed for improving robustness to RTF inaccuracies [10,11,12].…”

Optimized Speech Dereverberation From Probabilistic Perspective for Time Varying Acoustic Transfer Function

“…However, if the ATFs are time-varying, the deconvolution performance is greatly degraded even if the variation is quite small [7]. Sensitivity to small fluctuations due to a temperature change or to a small change in the speaker/microphone position can be improved by using a robust technique to estimate the ATFs, e.g., reducing the filter energy [8], spatial averaging [9], or pseudo-inverse calculation [10]. However, under large-fluctuations due to movement of the speaker's head, movement of the surrounding people, and obstacles located between the microphones and the speaker, the dereverberation performance of the MIF-based techniques is upper-limited.…”