Time-Aligned Spatial Upsampling of Spherical Microphone Array Recordings

With the Spherical Array Interpolation by Time Alignment (SARITA) method, the authors introduced an approach for spatial upsampling of spherical microphone array (SMA) signals (T. Lübeck, J. M. Arend, and C. Pörschmann, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 31, pp. 1163–1174 [2023]). The basic idea of this method is to perform the interpolation after time-aligning adjacent microphone signals. The upsampled SMA signals can be represented as spherical harmonic coefficients of much higher spatial order than is possible with the sparsely measured signals. Instead of impulse responses, the method is now applied to SMA recordings. Binaural decoding of upsampled SMA recordings is compared technically and perceptually to a baseline Ambisonics decoding. The results show that the SARITA method can also be applied to low-order array recordings and significantly improves their binaural reproduction.

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Publication Details

Journal
Journal of the Audio Engineering Society
Published
2024-10-16
DOI
https://doi.org/10.17743/jaes.2022.0166
Primary Topic
Speech and Audio Processing
Type
article
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article

Time-Aligned Spatial Upsampling of Spherical Microphone Array Recordings

Tim Lübeck, Johannes M. Arend, Christoph Pörschmann
Journal of the Audio Engineering Society
Speech and Audio Processing
article

Time-Aligned Spatial Upsampling of Spherical Microphone Array Recordings

Tim Lübeck, Johannes M. Arend, Christoph Pörschmann
article en

Abstract

With the Spherical Array Interpolation by Time Alignment (SARITA) method, the authors introduced an approach for spatial upsampling of spherical microphone array (SMA) signals (T. Lübeck, J. M. Arend, and C. Pörschmann, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 31, pp. 1163–1174 [2023]). The basic idea of this method is to perform the interpolation after time-aligning adjacent microphone signals. The upsampled SMA signals can be represented as spherical harmonic coefficients of much higher spatial order than is possible with the sparsely measured signals. Instead of impulse responses, the method is now applied to SMA recordings. Binaural decoding of upsampled SMA recordings is compared technically and perceptually to a baseline Ambisonics decoding. The results show that the SARITA method can also be applied to low-order array recordings and significantly improves their binaural reproduction.

Journal of the Audio Engineering SocietyVol. 72(10)
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Openalex Percentile: Top 80%
Speech and Audio Processing
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