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Sound Event Localization and Detection Using CRNN on Pairs of Microphones

Grondin, François, Glass, François, Sobieraj, Iwona and Plumbley, Mark D. (2019) Sound Event Localization and Detection Using CRNN on Pairs of Microphones In: The Detection and Classification of Acoustic Scenes and Events 2019 Workshop (DCASE2019), 2019-10-25-2019-10-26, New York, USA.

GrondinGlassSobierajP19-dcase.pdf - Accepted version Manuscript

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This paper proposes sound event localization and detection methods from multichannel recording. The proposed system is based on two Convolutional Recurrent Neural Networks (CRNNs) to perform sound event detection (SED) and time difference of arrival (TDOA) estimation on each pair of microphones in a microphone array. In this paper, the system is evaluated with a four-microphone array, and thus combines the results from six pairs of microphones to provide a final classification and a 3-D direction of arrival (DOA) estimate. Results demonstrate that the proposed approach outperforms the DCASE 2019 baseline system.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Grondin, François
Glass, François
Plumbley, Mark
Editors :
Mandel, Michael
Salamon, Justin
Ellis, Daniel P. W.
Date : October 2019
Funders : Signify, The European Union’s H2020 Framework Programme (H2020-MSCA-ITN-2014), EPSRC - Engineering and Physical Sciences Research Council
DOI : 10.33682/4v2a-7q02
Copyright Disclaimer : Copyright 2019 The Authors. This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit:
Uncontrolled Keywords : Sound event detection; Sound source localization; Time difference of arrival; Neural network
Related URLs :
Depositing User : Diane Maxfield
Date Deposited : 05 Nov 2019 12:24
Last Modified : 05 Nov 2019 12:24

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