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Gaussian Mixture Kalman predictive coding of lsfs

Subasingha, Shaminda; Murthi, Manohar N. and Andersen, Sören Vang LU (2008) IEEE International Conference on Acoustics, Speech, and Signal Processing, 2008 In 2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12 p.4777-4780
Abstract
Gaussian Mixture Model (GMM)-based predictive coding of line spectral frequencies (lsf's) has gained wide acceptance. In such coders, each mixture of a GMM can be interpreted as defining a linear predictive transform coder. In this paper we optimize each of these linear predictive transform coders using Kalman predictive coding techniques to present GMM Kalman predictive coding. In particular, we show how suitable modeling of quantization noise leads to an adaptive a-posteriori GMM that defines a signal-adaptive predictive coder that provides superior coding of lsfs in comparison with the baseline GMM predictive coder. Moreover, we show how running the Kalman predictive coders to convergence can be used to design a stationary predictive... (More)
Gaussian Mixture Model (GMM)-based predictive coding of line spectral frequencies (lsf's) has gained wide acceptance. In such coders, each mixture of a GMM can be interpreted as defining a linear predictive transform coder. In this paper we optimize each of these linear predictive transform coders using Kalman predictive coding techniques to present GMM Kalman predictive coding. In particular, we show how suitable modeling of quantization noise leads to an adaptive a-posteriori GMM that defines a signal-adaptive predictive coder that provides superior coding of lsfs in comparison with the baseline GMM predictive coder. Moreover, we show how running the Kalman predictive coders to convergence can be used to design a stationary predictive coding system which again provides superior coding of lsfs but now with no increase in run-time complexity over the baseline. (Less)
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author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
speech coding, vector quantization, Kalman filtering, Gaussian Mixture, Models
in
2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12
pages
4777 - 4780
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2008
external identifiers
  • wos:000257456703178
  • scopus:51449107656
ISSN
1520-6149
DOI
10.1109/ICASSP.2008.4518725
language
English
LU publication?
no
id
17169146-ac70-4c6c-b88f-85d1eb5b7b6e (old id 4092489)
date added to LUP
2013-10-17 10:56:21
date last changed
2017-01-01 05:43:37
@inproceedings{17169146-ac70-4c6c-b88f-85d1eb5b7b6e,
  abstract     = {Gaussian Mixture Model (GMM)-based predictive coding of line spectral frequencies (lsf's) has gained wide acceptance. In such coders, each mixture of a GMM can be interpreted as defining a linear predictive transform coder. In this paper we optimize each of these linear predictive transform coders using Kalman predictive coding techniques to present GMM Kalman predictive coding. In particular, we show how suitable modeling of quantization noise leads to an adaptive a-posteriori GMM that defines a signal-adaptive predictive coder that provides superior coding of lsfs in comparison with the baseline GMM predictive coder. Moreover, we show how running the Kalman predictive coders to convergence can be used to design a stationary predictive coding system which again provides superior coding of lsfs but now with no increase in run-time complexity over the baseline.},
  author       = {Subasingha, Shaminda and Murthi, Manohar N. and Andersen, Sören Vang},
  booktitle    = {2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12},
  issn         = {1520-6149},
  keyword      = {speech coding,vector quantization,Kalman filtering,Gaussian Mixture,Models},
  language     = {eng},
  pages        = {4777--4780},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Gaussian Mixture Kalman predictive coding of lsfs},
  url          = {http://dx.doi.org/10.1109/ICASSP.2008.4518725},
  year         = {2008},
}