NDLI: Deep and CNN fusion method for binaural sound source localisation

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Deep and CNN fusion method for binaural sound source localisation

Content Provider	IET Digital Library
Author	Jiang, Shilong Wu, Lulu Yuan, Peipei Sun, Yongheng Liu, Hong
Abstract	In binaural sound source localisation, front–back confusion is often the challenging problem when localising sources in the noisy or reverberant environments. Hence, a novel algorithm fusing deep and convolutional neural network (CNN) is proposed to address this issue. First, joint features, which consist of interaural level differences (ILDs) and cross-correlation function (CCF) within a lag range, are extracted from binaural signals. Second, with the extracted CCF–ILD features, CNN is used for the front–back classification task, while deep neural network is used for azimuth classification task. The front–back features extracted by the CNN can be leveraged as additional information for the sound source localisation task. Also, an angle-loss function is designed to avoid the overfitting problem and to improve the generalisation ability of this method in adverse acoustic conditions. Finally, two branches are concatenated and then followed by an output layer, which generates the posterior probability of azimuth angles, and the azimuth corresponding to the maximum posterior probability is chosen as the direction of sound source. Experimental results demonstrate the effectiveness of the authors’ method for front–back decision and azimuth estimation in noisy and reverberant environments.
Starting Page	511
Ending Page	516
Page Count	6
Volume Number	2020
e-ISSN	20513305
Issue Number	Issue 13, Jul (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/joe/2020/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/joe.2019.1207
Journal	The Journal of Engineering
Publisher	The Institution of Engineering and Technology
Publisher Date	2020-01-13
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	Acoustic Signal Processing Azimuth Classification Task Binaural Signal Binaural Sound Source Localisation CCF–ILD Features Extraction CNN Convolutional Neural Nets Convolutional Neural Network Correlation Method Cross-correlation Function Deep Neural Network Digital Signal Processing Feature Extraction Interaural Level Differences Maximum Posterior Probability Neural Computing Technique Probability Signal Classification Signal Processing And Detection Statistics
Content Type	Text
Resource Type	Article

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