Title: | Sound Source Localisation in Ambisonic Audio Using Peak Clustering |
Authors: | Green, Marc Murphy, Damian |
Date Issued: | Oct-2019 |
Citation: | M. Green & D. Murphy, "Sound Source Localisation in Ambisonic Audio Using Peak Clustering", Proceedings of the Detection and Classification of Acoustic Scenes and Events 2019 Workshop (DCASE2019), pages 79–83, New York University, NY, USA, Oct. 2019 |
Abstract: | Accurate sound source direction-of-arrival and trajectory estimation in 3D is a key component of acoustic scene analysis for many applications, including as part of polyphonic sound event detection systems. Recently, a number of systems have been proposed which perform this function with first-order Ambisonic audio and can work well, though typically performance drops when the polyphony is increased. This paper introduces a novel system for source localisation using spherical harmonic beamforming and unsupervised peak clustering. The performance of the system is investigated using synthetic scenes in first to fourth order Ambisonics and featuring up to three overlapping sounds. It is shown that use of second-order Ambisonics results in significantly increased performance relative to first-order. Using third and fourth-order Ambisonics also results in improvements, though these are not so pronounced. |
First Page: | 79 |
Last Page: | 83 |
DOI: | https://doi.org/10.33682/05my-4306 |
Type: | Article |
Appears in Collections: | Proceedings of the Detection and Classification of Acoustic Scenes and Events 2019 Workshop (DCASE2019) |
Files in This Item:
File | Size | Format | |
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DCASE2019Workshop_Green_18.pdf | 661.1 kB | Adobe PDF | View/Open |
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