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Analysis-by-synthesis speech coding with quantization noise modeling

Andersen, Sören Vang LU ; Kleijn, WB ; Jensen, SH and Hansen, E (1998) 32nd Asilomar Conference on Signals, Systems and Computers, 1998 p.333-337
Abstract
Iii analysis-by-synthesis linear predictive coding (AbS-LPC) an LPC synthesis filter is combined with an analysis-by-synthesis search of the excitation signal. The synthesis filter is an estimator for the speech signal given the excitation. However in most AbS-LPC algorithms this estimator has no explicit model of the quantization noise, which is present in the excitation signal. This paper describes quantization noise modeling in a vector AbS-LPC algorithm. Methods based on recursive Bayesian filtering and Kalman filtering are considered. Simulations indicate improved signal-to-noise ratios due to quantization noise modeling.
Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
CONFERENCE RECORD OF THE THIRTY-SECOND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2
pages
333 - 337
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
32nd Asilomar Conference on Signals, Systems and Computers, 1998
conference location
PACIFIC GROVE, CA, United States
conference dates
1998-11-01 - 1998-11-04
external identifiers
  • wos:000078743600061
  • scopus:0032267986
ISSN
1058-6393
language
English
LU publication?
no
id
5e92a1da-be70-402a-8851-f1b88fb61226 (old id 4092594)
date added to LUP
2016-04-01 15:22:10
date last changed
2022-03-22 04:06:54
@inproceedings{5e92a1da-be70-402a-8851-f1b88fb61226,
  abstract     = {{Iii analysis-by-synthesis linear predictive coding (AbS-LPC) an LPC synthesis filter is combined with an analysis-by-synthesis search of the excitation signal. The synthesis filter is an estimator for the speech signal given the excitation. However in most AbS-LPC algorithms this estimator has no explicit model of the quantization noise, which is present in the excitation signal. This paper describes quantization noise modeling in a vector AbS-LPC algorithm. Methods based on recursive Bayesian filtering and Kalman filtering are considered. Simulations indicate improved signal-to-noise ratios due to quantization noise modeling.}},
  author       = {{Andersen, Sören Vang and Kleijn, WB and Jensen, SH and Hansen, E}},
  booktitle    = {{CONFERENCE RECORD OF THE THIRTY-SECOND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2}},
  issn         = {{1058-6393}},
  language     = {{eng}},
  pages        = {{333--337}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Analysis-by-synthesis speech coding with quantization noise modeling}},
  year         = {{1998}},
}