Source Localization for Multiple Speech Sources Using Low Complexity Non-Parametric Source Separation and Clustering
(2011) In Signal Processing 91(8). p.1781-1788- Abstract
- This article presents a new method for localization of multiple concurrent speech sources that relies on simultaneous blind signal separation and direction of arrival (DOA) estimation, as well as a method to solve the intersection point selection problem that arises when locating multiple speech sources using multiple sensor arrays. The proposed method is based on a low complexity non-parametric blind signal separation method, making is suitable for real-time applications on embedded platforms. On top of reduced complexity in comparison to a previously presented method, the DOA estimation accuracy is also improved. Evaluation of the performance is done with both real recording and simulations, and a real-time prototype of the proposed... (More)
- This article presents a new method for localization of multiple concurrent speech sources that relies on simultaneous blind signal separation and direction of arrival (DOA) estimation, as well as a method to solve the intersection point selection problem that arises when locating multiple speech sources using multiple sensor arrays. The proposed method is based on a low complexity non-parametric blind signal separation method, making is suitable for real-time applications on embedded platforms. On top of reduced complexity in comparison to a previously presented method, the DOA estimation accuracy is also improved. Evaluation of the performance is done with both real recording and simulations, and a real-time prototype of the proposed method has been implemented on a DSP platform to evaluate the computational and the memory complexities in a real application. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/656b2c5d-8579-4a84-a8c9-2e87b08da390
- author
- Swartling, Mikael LU ; Sällberg, Benny and Grbic, Nedelko LU
- publishing date
- 2011-08
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Signal Processing
- volume
- 91
- issue
- 8
- pages
- 8 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:79955473942
- ISSN
- 0165-1684
- DOI
- 10.1016/j.sigpro.2011.02.002
- language
- English
- LU publication?
- no
- id
- 656b2c5d-8579-4a84-a8c9-2e87b08da390
- date added to LUP
- 2016-06-23 14:13:52
- date last changed
- 2022-01-30 04:42:35
@article{656b2c5d-8579-4a84-a8c9-2e87b08da390,
abstract = {{This article presents a new method for localization of multiple concurrent speech sources that relies on simultaneous blind signal separation and direction of arrival (DOA) estimation, as well as a method to solve the intersection point selection problem that arises when locating multiple speech sources using multiple sensor arrays. The proposed method is based on a low complexity non-parametric blind signal separation method, making is suitable for real-time applications on embedded platforms. On top of reduced complexity in comparison to a previously presented method, the DOA estimation accuracy is also improved. Evaluation of the performance is done with both real recording and simulations, and a real-time prototype of the proposed method has been implemented on a DSP platform to evaluate the computational and the memory complexities in a real application.}},
author = {{Swartling, Mikael and Sällberg, Benny and Grbic, Nedelko}},
issn = {{0165-1684}},
language = {{eng}},
number = {{8}},
pages = {{1781--1788}},
publisher = {{Elsevier}},
series = {{Signal Processing}},
title = {{Source Localization for Multiple Speech Sources Using Low Complexity Non-Parametric Source Separation and Clustering}},
url = {{http://dx.doi.org/10.1016/j.sigpro.2011.02.002}},
doi = {{10.1016/j.sigpro.2011.02.002}},
volume = {{91}},
year = {{2011}},
}