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Neural Network Based Adaptive Microphone Array System for Speech Enhancement

Grbic, Nedelko LU ; Dahl, Mattias and Claesson, Ingvar LU (1998) The 1998 IEEE International Joint Conference on Neural Networks. IEEE World Congress on Computational Intelligence In The 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence. 3. p.2180-2183
Abstract
Presents a microphone array system for use in handsfree mobile telephone equipment. The array is based on a fast and efficient “on-site” and “self-calibration” scheme. The performance in suppressing the interior car cabin noise and the far-end speech is approximately 17 dB, respectively, while maintaining the near-end speaker level. The near-end signal is almost undistorted. The performance of two different algorithms, normalized least-mean-square (NLMS) and fully connected backpropagation supervised neural network (MLP-NN) are evaluated. The proposed microphone array calibration scheme can also be used in other situations such as speech recognition devices
Please use this url to cite or link to this publication:
author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
The 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence.
volume
3
pages
4 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
The 1998 IEEE International Joint Conference on Neural Networks. IEEE World Congress on Computational Intelligence
external identifiers
  • Scopus:0031624936
ISBN
0-7803-4859-1
DOI
10.1109/IJCNN.1998.687198
language
English
LU publication?
no
id
0c4c2ea4-5a50-4494-88d9-0a9713d20887
date added to LUP
2016-06-23 14:40:08
date last changed
2016-06-29 10:17:41
@misc{0c4c2ea4-5a50-4494-88d9-0a9713d20887,
  abstract     = {Presents a microphone array system for use in handsfree mobile telephone equipment. The array is based on a fast and efficient “on-site” and “self-calibration” scheme. The performance in suppressing the interior car cabin noise and the far-end speech is approximately 17 dB, respectively, while maintaining the near-end speaker level. The near-end signal is almost undistorted. The performance of two different algorithms, normalized least-mean-square (NLMS) and fully connected backpropagation supervised neural network (MLP-NN) are evaluated. The proposed microphone array calibration scheme can also be used in other situations such as speech recognition devices},
  author       = {Grbic, Nedelko and Dahl, Mattias and Claesson, Ingvar},
  isbn         = {0-7803-4859-1},
  language     = {eng},
  pages        = {2180--2183},
  publisher    = {ARRAY(0x95704e8)},
  series       = {The 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence. },
  title        = {Neural Network Based Adaptive Microphone Array System for Speech Enhancement},
  url          = {http://dx.doi.org/10.1109/IJCNN.1998.687198 },
  volume       = {3},
  year         = {1998},
}