Analysis-by-synthesis speech coding with quantization noise modeling
(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:
https://lup.lub.lu.se/record/4092594
- author
- Andersen, Sören Vang LU ; Kleijn, WB ; Jensen, SH and Hansen, E
- publishing date
- 1998
- 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}}, }