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With the strong growth of assistive and personal listening devices, natural sound rendering over headphones is becoming a necessity for prolonged listening in multimedia and virtual reality applications. The aim of natural sound rendering is to naturally recreate the sound scenes with the spatial and timbral quality as natural as possible, so as to achieve a truly immersive listening experience. However, rendering natural sound over headphones encounters many challenges. This tutorial article presents signal processing techniques to tackle these challenges to assist human listening.

A sound zone control method is proposed, based on the frequency domain variable span trade-off filter (VAST). Existing VAST methods optimizes the sound field at a set of discrete points, while the proposed method uses kernel interpolation to instead optimize the sound field over a continuous region. When the loudspeaker positions are known, the performance can be improved further by applying a directional weighting to the interpolation procedure.

A sound zone control method is proposed, based on the frequency domain variable span trade-off filter (VAST). Existing VAST methods optimizes the sound field at a set of discrete points, while the proposed method uses kernel interpolation to instead optimize the sound field over a continuous region. When the loudspeaker positions are known, the performance can be improved further by applying a directional weighting to the interpolation procedure.

A method of interpolating the acoustic transfer function (ATF) between regions that takes into account both the physical properties of the ATF and the directionality of region configurations is proposed. Most spatial ATF interpolation methods are limited to estimation in the region of receivers. A kernel method for region-to-region ATF interpolation makes it possible to estimate the ATFs for both source and receiver regions from a discrete set of ATF measurements.

Sound field analysis and reconstruction has been a topic of intense research in the last decades for its multiple applications in spatial audio processing tasks. In this context, the identification of the direct and reverberant sound field components is a problem of great interest, where several solutions exploiting spherical harmonics representations have already been proposed.

Personal audio systems with multiple sound zones for listeners to enjoy different music/audio contents privately in a shared physical space have attracted great research interest in the past two decades. Acoustic Contrast Control (ACC) is one of the most popular methods for generating multiple personal sound zones because it produces the minimum inter-zone interference. However, the ACC method has been found to be inferior to the pressure matching method in terms of sound quality due to an uneven frequency response and nonuniform spatial sound field distribution in the bright zone.

In this paper, we present a novel framework of beamforming robust for a microphone array rotation. In most array signal processing methods, the time-invariant transfer system from a source to a microphone is assumed for calculating a spatial filter. This assumption makes it difficult to use the microphone array in real situations since sources and the microphone array may move. In this work, we focus on one such movement, the array’s rotation. The key in our method is to use a regularly circular microphone array where microphones are equally spaced on a circle’s circumference.