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This document illustrates how to process the signals from the microphones of a rigid-sphere higher-order ambisonic microphone array so that they are encoded with N3D normalization and ACN channel order and thereby can be used with the standard ambisonic software tools such as SPARTA and the IEM Plugin Suite. A MATLAB script is provided.

"Perceptual Evaluation of Mitigation Approaches of Impairments due to Spatial Undersampling in Binaural Rendering of Spherical Microphone Array Data : Dry Acoustic Environments" Suplementary Materials of the listening experiment: _______________________________________________________________________________________________________ This repository contains a set of static stimuli for frontal and lateral source positions as tested in the MUSHRA listening experiment. Furthermore, statistical results are presented as excel sheets. Please note that the listening experiments were conducted with AKG K702 Headphones. All binaural signals were equalized accordingly as proposed in [1]. A set of headphone compensation filters is provided in this repository as well. [1] Bernschütz, B. (2016). Microphone Arrays and Sound Field Decomposition for Dynamic Binaural Recording. Technische Universität Berlin. https://doi.org/10.14279/depositonce-5082 _______________________________________________________________________________________________________ Contact: Tim Lübeck TH Köln - University of Applied Sciences Institute of Communications Engineering Department of Acoustics and Audio Signal Processing Betzdorfer Str. 2, D-50679 Cologne, Germany https://www.th-koeln.de/personen/tim.luebeck/

International audience; Spherical microphone arrays are used to capture spatial sound fields, which can then be rendered via headphones. Insight into perceptual properties of sensor self-noise is valuable in the design and construction process of such arrays. We use the Real-Time Spherical Array Renderer (ReTiSAR) to analyze the frequency-dependent white-noise-gain, i.e. propagation of wanted and unwanted signals through the processing pipeline. In this contribution, we demonstrate an instrumental evaluation for a large set of array and rendering configurations. Latter strongly influence the rendered spectral balance and overall level of spatially uniformly distributed self-noise. Additionally, a dependency on head rotation yielding a change in the reproduced coloration is confirmed for the case of spatially non-uniform noise.