Laura Fuster

Room compensation in wave field synthesis by means of multichannel inversion

In the reproduction of sound using loudspeakers, the listening room adds echoes not considered by the reproduction system deteriorating the rendered acoustic field. Wave field synthesis is a 3D audio reproduction system, which allows synthesizing a realistic sound field in a wide area by using a large number of loudspeakers arrays. This paper proposes a room compensation approach based on a multichannel inverse filter bank that corrects the room effects at selected points within the listening area. Points are selected in order to allow a huge sweet spot disregarding the quality of the room. As a difference with previous works, this approach solves directly the multiple-input/multiple-output inverse system without simplifications, thus obtaining the best bank of inverse filters for the room to be compensated. Efficient mathematical algorithms to make affordable the computation of this filter bank are proposed. A carefully developed laboratory experiment to validate the method is also reported. Finally, an evaluation of the computational power required to run the filter bank in real time is presented.

Adaptive Filtered-x Algorithms for Room Equalization Based on Block-Based Combination Schemes

Room equalization has become essential for sound reproduction systems to provide the listener with the desired acoustical sensation. Recently, adaptive filters have been proposed as an effective tool in the core of these systems. In this context, this paper introduces different novel schemes based on the combination of adaptive filters idea: a versatile and flexible approach that permits obtaining adaptive schemes combining the capabilities of several independent adaptive filters. In this way, we have investigated the advantages of a scheme called combination of block-based adaptive filters which allows a blockwise combination splitting the adaptive filters into nonoverlapping blocks. This idea was previously applied to the plant identification problem, but has to be properly modified to obtain a suitable behavior in the equalization application. Moreover, we propose a scheme with the aim of further improving the equalization performance using the a priori knowledge of the energy distribution of the optimal inverse filter, where the block filters are chosen to fit with the coefficients energy distribution. Furthermore, the biased block-based filter is also introduced as a particular case of the combination scheme, especially suited for low signal-to-noise ratios (SNRs) or sparse scenarios. Although the combined schemes can be employed with any kind of adaptive filter, we employ the filtered-x improved proportionate normalized least mean square algorithm as basis of the proposed algorithms, allowing to introduce a novel combination scheme based on partitioned block schemes where different blocks of the adaptive filter use different parameter settings. Several experiments are included to evaluate the proposed algorithms in terms of convergence speed and steady-state behavior for different degrees of sparseness and SNRs.

Nonlinear filtered-X second-order adaptive volterra filters for listening-room compensation

The presence of nonlinearities as well as reverberation effects severely degrades the audio quality in sound reproduction systems. In this context, many adaptive strategies have been developed to compensate for room effects. However, when nonlinear distortion becomes significant, room equalization requires the introduction of suitable solutions to tackle this problem. Linearization of loudspeakers has been deeply investigated but its combination with room equalization systems may not be so straightforward, mainly when the nonlinearities present memory. In this paper, the nonlinear system has been modeled as a Volterra filter that represents the loudspeaker tandemly connected to a linear filter that corresponds to the electroacoustic path including the enclosure and the microphone setup. Based on this structure, we introduce a nonlinear filtered-x second-order adaptive Volterra filter that uses the virtual path concept to preprocess the audio signals. Simulation results validate the performance of the new approach.

STEADY-STATE ANALYSIS OF BIASED FILTERED-X ALGORITHMS FOR ADAPTIVE ROOM EQUALIZATION

This paper provides an analysis of the steady-state behavior of two biased adaptive algorithms recently introduced for listening room compensation, the biased filtered-x normalized least mean squares (Fx-BNLMS) and the biased filtered-x improved proportionate NLMS (Fx-BIPNLMS). We give theoretical results that show that the biased algorithms can outperform the unbiased ones in terms of the mean square error, especially in low signal-to-noise ratio (SNR) scenarios. Moreover, for impulse responses exhibiting high sparse-ness, the improved proportionate algorithms achieve faster convergence than the standard NLMS. Thereby, the advantages of the Fx-BIPNLMS algorithm are justified theoretically in terms of the excess mean square error. Simulation results show that there is a relatively good match between theory and practice, especially for low μ values.

Combination of filtered-x adaptive filters for nonlinear listening-room compensation

Audio quality in sound reproduction systems can be severely degraded due to system nonlinearities and reverberation effects. In this context, linearization of loudspeakers has been deeply investigated but its combination with room equalization is not straightforward, mainly when the nonlinearities present memory. In this paper, a method relying on the convex combination of two linear filters using the filtered-x LMS (FXLMS) algorithm and based on the virtual path concept to preprocess audio signals is presented for nonlinear room compensation. It is shown that the combination of two linear adaptive filters behaves similarly to the filtered-x second-order adaptive Volterra (NFXLMS) filter. Moreover the new approach is computationally more efficient and avoids the generation of higher harmonics. Experimental results validate the performance of the new approach.

Efficient implementation of matrix recursions in the multichannel affine projection algorithm for multichannel sound

Multichannel adaptive affine projection algorithms (multichannel AP) are currently under development for multichannel audio applications, mainly for transaural audio reproduction. These algorithms present several advantages for real time systems such as moderate computational cost, good stability, and adjustable convergence speed. However the basic version of the AP algorithm needs to be optimized to be used on digital signal processors working on real time. Thus several variants of AP and its fast version (FAP) have been developed. Regarding its computational cost and real time implementation, an N /spl times/ N inverse matrix have to be calculated in each algorithm iteration, being N the affine projection order. This paper presents a comparison between several versions of the AP algorithm for real time multichannel audio and proposes a series of recommendations, such as the initialization parameters, to use the variants of the AP algorithm in multichannel sound.