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Online Blind Speech Extraction based on a Locally Quadratic Kurtosis Criteria and a Preprocessing Automatic Gain Controller

Sällberg, Benny; Grbic, Nedelko LU and Claesson, Ingvar LU (2007) ELMAR-2007 In IEEE ELMAR 2007 p.139-142
Abstract
This paper focuses on realtime speech extraction using blind adaptive beamforming. The speech extraction is carried out using an approximation of the kurtosis measure in a subband domain. The introduced kurtosis approximation is an improvement of a recently proposed approximation technique where a locally quadratic criterion was solved at each iteration. The improvement introduced in this paper regards an approach to normalize this same criterion using a pre-processing automatic gain control unit, and thereby making the algorithm invariant to input signal scales. The proposed method outperforms the recent technique in terms of signal to interference ratio improvement. In addition, the increased memory consumption and processing load due to... (More)
This paper focuses on realtime speech extraction using blind adaptive beamforming. The speech extraction is carried out using an approximation of the kurtosis measure in a subband domain. The introduced kurtosis approximation is an improvement of a recently proposed approximation technique where a locally quadratic criterion was solved at each iteration. The improvement introduced in this paper regards an approach to normalize this same criterion using a pre-processing automatic gain control unit, and thereby making the algorithm invariant to input signal scales. The proposed method outperforms the recent technique in terms of signal to interference ratio improvement. In addition, the increased memory consumption and processing load due to the proposed improvement is comparably low and this is often desirable in a realtime digital signal processor (DSP) implementation. Further, a real-time implementation of the method is conducted and results with real data is presented. (Less)
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author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
IEEE ELMAR 2007
pages
4 pages
conference name
ELMAR-2007
external identifiers
  • scopus:47349107419
ISBN
978-953-7044-05-3
DOI
10.1109/ELMAR.2007.4418816
language
English
LU publication?
no
id
5c4b13fa-1c8d-41d9-8648-a6132c78c3a8
date added to LUP
2016-06-23 16:51:19
date last changed
2017-01-01 08:29:04
@inproceedings{5c4b13fa-1c8d-41d9-8648-a6132c78c3a8,
  abstract     = {This paper focuses on realtime speech extraction using blind adaptive beamforming. The speech extraction is carried out using an approximation of the kurtosis measure in a subband domain. The introduced kurtosis approximation is an improvement of a recently proposed approximation technique where a locally quadratic criterion was solved at each iteration. The improvement introduced in this paper regards an approach to normalize this same criterion using a pre-processing automatic gain control unit, and thereby making the algorithm invariant to input signal scales. The proposed method outperforms the recent technique in terms of signal to interference ratio improvement. In addition, the increased memory consumption and processing load due to the proposed improvement is comparably low and this is often desirable in a realtime digital signal processor (DSP) implementation. Further, a real-time implementation of the method is conducted and results with real data is presented.},
  author       = {Sällberg, Benny and Grbic, Nedelko and Claesson, Ingvar},
  booktitle    = {IEEE ELMAR 2007},
  isbn         = {978-953-7044-05-3},
  language     = {eng},
  pages        = {139--142},
  title        = {Online Blind Speech Extraction based on a Locally Quadratic Kurtosis Criteria and a Preprocessing Automatic Gain Controller},
  url          = {http://dx.doi.org/10.1109/ELMAR.2007.4418816 },
  year         = {2007},
}