Performance Analysis Of Binaural Signal Matching (BSM) in the Time-Frequency Domain

Ami Berger, Vladimir Tourbabin, Jacob Donley, Zamir Ben-Hur, Boaz Rafaely
Electrical Engineering and Systems Science, Audio and Speech Processing, Audio and Speech Processing (eess.AS)
A. Berger, V. Tourbabin, J. Donley, Z. Ben-Hur, and B. Rafaely, Performance analysis of binaural signal matching (BSM) in the time-frequency domain, in Proceedings of the 24th International Congress on Acoustics (ICA 2022), ABS-0302, 2022
2023-11-22 00:00:00
The capture and reproduction of spatial audio is becoming increasingly popular, with the mushrooming of applications in teleconferencing, entertainment and virtual reality. Many binaural reproduction methods have been developed and studied extensively for spherical and other specially designed arrays. However, the recent increased popularity of wearable and mobile arrays requires the development of binaural reproduction methods for these arrays. One such method is binaural signal matching (BSM). However, to date this method has only been investigated with fixed matched filters designed for long audio recordings. With the aim of making the BSM method more adaptive to dynamic environments, this paper analyzes BSM with a parameterized sound-field in the time-frequency domain. The paper presents results of implementing the BSM method on a sound-field that was decomposed into its direct and reverberant components, and compares this implementation with the BSM computed for the entire sound-field, to compare performance for binaural reproduction of reverberant speech in a simulated environment.
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