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Journal Article

Ambisonics Room Impulse Response Estimation From a Single Omnidirectional Measurement Using Deep Neural Networks

Authors: Yu, Wangyang; Kleijn, W. Bastiaan

Journal of the Audio Engineering Society · Volume 72 · Issue 12 · pp. 884–900 · December 2024

Abstract

Mapping a room impulse response (RIR) to its Ambisonics representation is not always feasible. However, by adding a weak assumption (i.e., the existence of at least two perpendicular walls in the environment), the Ambisonics representation is restricted to be one of a finite set, with known transformations between the set entries. This makes mapping the omnidirectional RIR to the Ambisonics RIR (ARIR) possible. The authors solve the mapping problem with a convolutional neural network and multi-task variational autoencoder. The room is assumed to be rectangular. The proposed method is based on the image source method with frequency independent reflection coefficients exclusively. The authors focus on the early part of RIRs, where the directional information lies. This method requires only a single RIR. Generalizing to the real world, measurements can obviate the need for specialized hardware for Ambisonics measurement. The proposed method can achieve an SNR of 17.62 dB on estimated first-order ARIRs and 16.15 dB on estimated third-order ARIRs.

Details

Publication
Journal of the Audio Engineering Society
Volume
72
Issue
12
Pages
884–900
Publication date
December 12, 2024
Affiliation
Department of Microelectronics, Signal Processing Systems, Delft University of Technology, Delft, The Netherlands; School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand (See document for exact affiliation information.)
Type
Journal Article