NDLI: Single source bins detection-based localisation scheme for multiple speech sources

Content Provider	IET Digital Library
Author	Jia, Maoshen Sun, Jundai Deng, Feng Sun, Junyue
Abstract	A single source bins (SSBs) detection based multiple source localisation scheme is proposed. This scheme is based on detecting the SSBs in mixture signals that are only derived from one source. Specifically, after proposing a ‘DOA convergence’ assumption, K-means clustering algorithm is used for SSBs detecting. Thus, the multiple source localisation is converted to a single source one among these SSBs. Moreover, the proposed SSBs detection is applicable to other localisation methods and not limited to specific microphone topology. Experimental results demonstrate the localisation accuracy of the proposed method outperforms the localisation approaches which are based on single source zone detection.
Starting Page	430
Ending Page	432
Page Count	3
ISSN	00135194
Volume Number	53
e-ISSN	1350911X
Issue Number	Issue 6, Mar (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/53/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2017.0171
Journal	Electronics Letters
Publisher Date	2017-02-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Direction of Arrival Estimation DOA Convergence K-means Clustering Algorithm Multiple Speech Source Pattern Clustering Single Source Bins Detection-based Multiple Localisation Scheme Speech And Audio Signal Processing Speech Processing Speech Processing Technique SSB
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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