Wolfgang Herbordt

Active listening room compensation for massive multichannel sound reproduction systems using wave-domain adaptive filtering

The acoustic theory for multichannel sound reproduction systems usually assumes free-field conditions for the listening environment. However, their performance in real-world listening environments may be impaired by reflections at the walls. This impairment can be reduced by suitable compensation measures. For systems with many channels, active compensation is an option, since the compensating waves can be created by the reproduction loudspeakers. Due to the time-varying nature of room acoustics, the compensation signals have to be determined by an adaptive system. The problems associated with the successful operation of multichannel adaptive systems are addressed in this contribution. First, a method for decoupling the adaptation problem is introduced. It is based on a generalized singular value decomposition and is called eigenspace adaptive filtering. Unfortunately, it cannot be implemented in its pure form, since the continuous adaptation of the generalized singular value decomposition matrices to the variable room acoustics is numerically very demanding. However, a combination of this mathematical technique with the physical description of wave propagation yields a realizable multichannel adaptation method with good decoupling properties. It is called wave domain adaptive filtering and is discussed here in the context of wave field synthesis.

Adaptive Beamforming for Audio Signal Acquisition

This chapter provides an overview of adaptive beamforming techniques for speech and audio signal acquisition. We review basic concepts of optimum adaptive antenna arrays and show how these methods may be applied to meet the requirements of audio signal processing. In particular, we derive optimum beamformers using time-domain least-squares instead of frequency-domain minimum mean-squares criteria, and, thereby, are not constrained by the commonly used narrow-band and stationarity assumptions. We thus obtain a more general representation of various beamforming aspects relevant to our application. From this, a robust generalized sidelobe canceller (GSC) [1] results as an attractive solution for practical audio acquisition systems. Moreover, the general theoretical framework leads to new insights for the GSC behavior in complex practical situations.

Frequency-domain integration of acoustic echo cancellation and a generalized sidelobe canceller with improved robustness

For hands-free acoustic human/machine interfaces, as required, e.g., for automatic speech recognition, teleconferencing, and other multimedia services, microphone arrays using generalized sidelobe cancellers (GSCs) in conjunction with acoustic echo cancellation (AEC) can be efficiently applied for optimum communication. This contribution first devises a hew structure for combining AEC and GSC in the frequency domain. We show that computational complexity is reduced by more than a factor of ten compared to a time-domain arrangement. Second, robustness issues of the GSC adaptation mechanism are addressed. We illustrate how robust adaptation is assured in the new structure. Third, we propose alternatives for the fixed beamformer part of the GSC, which allow to specify (a) the width of the target tracking region and (b) improve the suppression of low frequencies. GSC robustness constraints are included using linear optimization with configurable penalty functions.

An integrated real-time system for immersive audio applications

A real-time system for immersive audio applications is presented. Sound sources are recorded using a microphone array whose beam is steered according to the output of an acoustic source localization and tracking system. The output of the beamformer (BF) along with the source position updates are continuously transmitted to a wave field synthesis (WFS) system. By using WFS, the sound sources in the recording room are rendered in the reproduction room with the correct spatial cues.

An acoustic human-machine front-end for multimedia applications

A concept of robust adaptive beamforming integrating stereophonic acoustic echo cancellation is presented which reconciles the need for low-computational complexity and efficient adaptive filtering with versatility and robustness in real-world scenarios. The synergetic combination of a robust generalized sidelobe canceller and a stereo acoustic echo canceller is designed in the frequency domain based on a general framework for multichannel adaptive filtering in the frequency domain. Theoretical analysis and real-time experiments show the superiority of this concept over comparable time-domain approaches in terms of computational complexity and adaptation behaviour. The real-time implementation confirms that the concept is robust and meets well the practical requirements of real-world scenarios, which makes it a promising candidate for commercial products.

Multichannel Bin-Wise Robust Frequency-Domain Adaptive Filtering and Its Application to Adaptive Beamforming

Least-squares error (LSE) or mean-squared error (MSE) optimization criteria lead to adaptive filters that are highly sensitive to impulsive noise. The sensitivity to noise bursts increases with the convergence speed of the adaptation algorithm and limits the performance of signal processing algorithms, especially when fast convergence is required, as for example, in adaptive beamforming for speech and audio signal acquisition or acoustic echo cancellation. In these applications, noise bursts are frequently due to undetected double-talk. In this paper, we present impulsive noise robust multichannel frequency-domain adaptive filters (MC-FDAFs) based on outlier-robust M-estimation using a Newton algorithm and a discrete Newton algorithm, which are especially designed for frequency bin-wise adaptation control. Bin-wise adaptation and control in the frequency-domain enables the application of the outlier-robust MC-FDAFs to a generalized sidelobe canceler (GSC) using an adaptive blocking matrix for speech and audio signal acquisition. It is shown that the improved robustness leads to faster convergence and to higher interference suppression relative to nonrobust adaptation algorithms, especially during periods of strong interference

Efficient frequency-domain realization of robust generalized, sidelobe cancellers

This paper deals with hands-free acoustical front-ends for human/machine interaction in competing talker situations using efficient frequency-domain implementations of a robust generalized sidelobe canceller (GSC). A new scheme is devised which leads to a factor of three of computational savings. The GSC tracking behavior is not impaired as the block lengths are kept sufficiently small.

Analysis of blocking matrices for generalized sidelobe cancellers for non-stationary broadband signals

This contribution relates the robust generalized sidelobe canceller (RGSC) with an adaptive blocking matrix (ABM) after Hoshuyama et al. for non-stationary broadband signals with linearly constrained minimum variance (LCMV) beamformers. While alternative approaches only exploit spatial wave field characteristics, it is shown that the ABM introduces dependency on the desired signal power spectral density (PSD) into the array look-direction constraints. The ABM yields better interference suppression than for stationary frequency independent look-direction constraints, since the ABM does not suppress frequencies without desired signal components.

Application of a double-talk resilient DFT domain adaptive filter for bin-wise stepsize controls to adaptive beamforming

Summary form only given. In adaptive filtering, undetected noise bursts often disturb the adaptation and may lead to instabilities and divergence of the adaptive filter. The sensitivity against noise bursts increases with the convergence speed of the adaptive filter and limits the performance of signal processing methods where fast convergence is required. Typical applications which are sensitive against noise bursts are adaptive beamforming for audio signal acquisition or acoustic echo cancellation, where noise bursts are frequent due to undetected double-talk. In this paper, we apply double-talk resistant adaptive filtering (Gaensler (1998)) using a nonlinear optimization criterion to adaptive beamforming in the discrete Fourier transform domain for bin-wise adaptation controls. We show the efficiency of double-talk resilient adaptive filtering for a generalized sidelobe canceller for speech and audio signal acquisition. The improved robustness leads to faster convergence, to higher noise reduction, and to a better output signal quality in turn.

Using artificially reverberated training data in distant-talking ASR

Automatic Speech Recognition (ASR) in reverberant rooms can be improved by choosing training data from the same acoustical environment as the test data. In a real-world application this is often not possible. A solution for this problem is to use speech signals from a close-talking microphone and reverberate them artificially with multiple room impulse responses. This paper shows results on recognizers whose training data differ in size and percentage of reverberated signals in order to find the best combination for data sets with different degrees of reverberation. The average error rate on a close-talking and a distant-talking test set could thus be reduced by 29% relative.