Two vs. Four-Channel Sound Event Localization and Detection

TL;DR

This paper compares the performance of sound event localization and detection models using different audio input formats, revealing that 2-channel audio can still effectively localize sound sources despite reduced information.

Contribution

It provides a novel analysis of how binaural and stereo inputs impact SELD performance, especially in complex acoustic scenes, highlighting the viability of simpler audio formats.

Findings

Binaural and stereo inputs perform well in lateral localization.

Performance degrades with fewer audio channels.

Effect of scene complexity on localization accuracy.

Abstract

Sound event localization and detection (SELD) systems estimate both the direction-of-arrival (DOA) and class of sound sources over time. In the DCASE 2022 SELD Challenge (Task 3), models are designed to operate in a 4-channel setting. While beneficial to further the development of SELD systems using a multichannel recording setup such as first-order Ambisonics (FOA), most consumer electronics devices rarely are able to record using more than two channels. For this reason, in this work we investigate the performance of the DCASE 2022 SELD baseline model using three audio input representations: FOA, binaural, and stereo. We perform a novel comparative analysis illustrating the effect of these audio input representations on SELD performance. Crucially, we show that binaural and stereo (i.e. 2-channel) audio-based SELD models are still able to localize and detect sound sources laterally quite well, despite overall performance degrading as less audio information is provided. Further, we segment our analysis by scenes containing varying degrees of sound source polyphony to better understand the effect of audio input representation on localization and detection performance as scene conditions become increasingly complex.