Evaluation of Sensor Self-Noise in Binaural Rendering of Spherical Microphone Array Signals

Hannes Helmholz, Jens Ahrens, David L. Alon, Sebastia V. Amengual Gari, Ravish Mehra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Spherical microphone arrays are used to capture spatial sound fields, which can then be rendered via headphones. We use the Real-Time Spherical Array Renderer (ReTiSAR) to analyze and auralize the propagation of sensor self-noise through the processing pipeline. An instrumental evaluation confirms a strong global influence of different array and rendering parameters on the spectral balance and the overall level of the rendered noise. The character of the noise is direction independent in the case of spatially uniformly distributed noise. However, timbre of the rendered self-noise changes with head orientation in the case of spatially non-uniform noise. We determine audibility thresholds of the coloration artifact during head rotations for different array configurations in a perceptual user study.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Pages161-165
Number of pages5
ISBN (Electronic)9781509066315
DOIs
StatePublished - 1 May 2020
Externally publishedYes
Event2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain
Duration: 4 May 20208 May 2020

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2020-May
ISSN (Print)1520-6149

Conference

Conference2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Country/TerritorySpain
CityBarcelona
Period4/05/208/05/20

Keywords

  • Binaural rendering
  • Real-time signal processing
  • Sensor self-noise
  • Spherical microphone arrays

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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