Psychoacoustics parameters are widely employed in automotive field for objective evaluation of Sound Quality (SQ) of vehicle cabins and their components. The standard approach relies on binaural recordings from which numerical values and curves are calculated. In addition, head-locked binaural listening playback can be performed. The Virtual Reality (VR) technology recently started to diffuse also in automotive field, bringing new possibilities for enhanced and immersive listening sessions, thanks to the usage of massive microphone arrays instead of binaural microphones.In this paper, we combine both solutions: the principal SQ parameters are derived from multichannel recordings. This allows computing a map of direction-dependent values of SQ parameters. The acquisition system consists in a spherical microphone array with 32 capsules and a multiple-lens camera for capturing a panoramic equirectangular background image. The audio recording is encoded into High Order Ambisonics (HOA) format for being compared with a classic omnidirectional microphone and into Spatial PCM Sampling (SPS) format for producing 360° equirectangular color maps. The SPS encoding is used to plot over the background image the distribution of SPL values in dB (A) and of the SQ parameters: by adding to them the directional information, it results into a novel 360° diagnostic tool for localizing the most annoying sources.Furthermore, the playback of the HOA soundtrack can be performed both on a loudspeaker rig inside an Ambisonics listening room or on binaural headphones attached to a Head Mounted Display (HMD), benefiting from head-tracking and personalized Head Related Transfer Functions (HRTFs), allowing to make quick subjective evaluations with a degree of realism unattainable with the older static binaural approach.
Direction Specific Analysis of Psychoacoustics Parameters inside Car Cockpit: A Novel Tool for NVH and Sound Quality
Sae Technical Papers
11th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference ; 2020
2020-09-30
Conference paper
English
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