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

PubDate: Oct 2022

Teams: Ben-Gurion University of the Negev；Reality Labs

Writers: Ami Berger, Vladimir Tourbabin, Jacob Donley, Zamir Ben-Hur, Boaz Rafaely

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

Abstract

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 aims to analyze 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, comparing it to the BSM computed for the entire sound-field, evaluating performance for binaural reproduction of reverberant speech in a simulated environment.