Comparison of Mitigation Approaches of Spatial Undersampling Artifacts in Spherical Microphone Array Data Auralizations
* Präsentierender Autor
Zusammenfassung:Spherical Microphone Arrays (SMAs) are widely used to capture spatial sound fields, that can then be rendered in various virtual acoustic environment (VAE) formats including binaural synthesis.However, some practical limitations have significant impact on the accuracy of the rendered VAE. On the one hand, the limited number of microphone capsules leads to spatial undersampling of the surrounding sound field, inducing spatial aliasing artifacts on the capturing side. On the other hand, the order-limited spherical harmonics representation results in truncation errors on the rendering side. Several approaches have been presented in research to mitigate these impairments. To our knowledge, there is no study available that compares the different methods directly in terms of their effectiveness. In this work, we present a comprehensive comparison of state-of-the-art undersampling mitigation algorithms, with a focus on binaural reproduction of SMA data. We give an overview of the fundamental concepts of the different approaches and based on a technical evaluation we discuss their influence on the binaural reproduction.