Signal Processing Algorithms for Adaptive Loudspeaker-Based Binaural Audio Reproduction

Zusatztext

Spatial audio reproduction offers a range of promising applications in the context of augmented and virtual reality, for example, immersive teleconferencing. Binaural signal reproduction involves creating separate audio signals for each ear, allowing for natural listening and hence enabling the listener to perceive immersion into a recorded or synthesized acoustic scene. Loudspeaker-based binaural audio reproduction requires to equalize the acoustic direct path and to attenuate the crosstalk by means of a crosstalk cancellation (CTC) filter network. Compared to headphone-based reproduction, loudspeaker-based reproduction offers advantages, such as enhanced externalization. However, today's loudspeaker-based binaural audio reproduction systems suffer from model errors that lead to objectively reduced performance metrics and poor subjective performance in localizing virtual sound sources. To address the limitations of current loudspeaker-based reproduction systems, the concept for adaptive CTC systems, featuring microphones positioned at the listeners ears, is presented. This setup enables to adapt the CTC filters to the characteristics of the listener and the acoustics of the reproduction room so that detrimental model errors can be avoided. Towards this goal, sophisticated signal processing algorithms are developed for identifying time-varying acoustic systems and for designing CTC filters. These algorithms are related and compared to state-of-the-art methods, and they are evaluated independently and within adaptive CTC systems. The methodology involves both theoretical development of algorithms and experimental validation through simulations and acoustic measurements.

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