Quantization properties of transmission parameters in linear predictive systems

Viswanathan, R.; Makhoul, John

doi:10.1109/tassp.1975.1162675

Cited by 195 publications

(40 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The well known Levinson-Durbin algorithm allows the solution of the system of equations given in (8) by operating recursive iterations of the order P and hence revealing three interesting sets of parameters, namely, the predictive coefficients (a i ), the energy prediction coefficients ( E i ) and the reflection coefficients (k i ). For more details on this method one should refer to references [9,10].…”

Section: Lpc Coefficient Determinationmentioning

confidence: 99%

Design of two blocks of a speech coding system to be implemented on an FPGA based card

Benmakhlouf¹,

Mekaoui²,

Ghoumid³

2013

WIT Transactions on Information and Communication Technologies

View full text Add to dashboard Cite

The main aim of this paper is concerned with modern telecommunications systems which involve modern methods of coding, encryption and decryption of speech signals. For a long time, for the transmission of a speech signal analog telecommunications systems have been used. Because of unexpected and unavoidable interference, wave fading perturbations and different kinds of noise occurring in the channel, it was not possible to detect and receive the same transmitted speech signal. Consequently, digital systems have steadily replaced the former. Here, we have simulated two blocks of such systems, namely the source coding block and the encryption/decryption block. We tested them by listening to the synthesized signals via headphones and using a simulation operated using Simulink of the source software Matlab. Although metallic in their tonalities, results were found to be acceptable.

show abstract

Section: Lpc Coefficient Determinationmentioning

confidence: 99%

Design of two blocks of a speech coding system to be implemented on an FPGA based card

Benmakhlouf¹,

Mekaoui²,

Ghoumid³

2013

WIT Transactions on Information and Communication Technologies

View full text Add to dashboard Cite

show abstract

“…For lossy coding, several quantization algorithms of PARCOR coefficients, also known as reflection coefficients, have been extensively investigated [5][6][7][8]. However, with G.711.0, there is a need for such a quantization algorithm for lossless coding.…”

Section: Introductionmentioning

confidence: 99%

Low-complexity PARCOR coefficient quantization and prediction order estimation designed for entropy coding of prediction residuals

Kamamoto

Moriya

Harada

et al. 2013

Acoust. Sci. & Tech.

View full text Add to dashboard Cite

This paper presents a set of low-complexity tools used in lossless coding of G.711 bitstream, based on linear prediction. One is an algorithm for quantizing the PARCOR/reflection coefficients and the other is an estimation method for the optimal prediction order. Both tools are based on a criterion that minimizes the entropy of the prediction residual signal and can be implemented in fixed-point arithmetic at very low-complexity. Since proposed methods show efficient performance in terms of compression and complexity, they are adopted in the Recommendation ITU-T G.711.0, a new standard for lossless compression of G.711 (A-law/ -law logarithmic PCM) payload.

show abstract

“…A coding scheme exploiting this model would replace°conventional reflection coefficients (or log area ratios [1]) with©¡°coefficients distributed over a°0 3 2 global order, plus a codeword to index the optimal filter topology. The quality compromise found by adjusting these specifications (in addition to a classical coefficient quantization system) may allow to reach a better coding quality at a lower bit rate than unspecialized AR models.…”

Section: Potential Applicationsmentioning

confidence: 99%

“…Their parameters, the reflection coefficients, have a good robustness to noise and quantization effects [1]. These filters also present a formal analogy with the process of wave propagation into lossless discrete acoustic tube models (possibly used as vocal tract models) [2].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Signal modeling with non-uniform topology lattice filters

Krstulović

Bimbot

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)

View full text Add to dashboard Cite

This article presents a new class of constrained and specialized Auto-Regressive (AR) processes. They are derived from lattice filters where some reflection coefficients are forced to zero at a priori locations. Optimizing the filter topology allows to build parametric spectral models that have a greater number of poles than the number of parameters needed to describe their location. These NUT (Non-Uniform Topology) models are assessed by evaluating the reduction of modeling error with respect to conventional AR models.

show abstract

Quantization properties of transmission parameters in linear predictive systems

Cited by 195 publications

References 9 publications

Design of two blocks of a speech coding system to be implemented on an FPGA based card

Design of two blocks of a speech coding system to be implemented on an FPGA based card

Low-complexity PARCOR coefficient quantization and prediction order estimation designed for entropy coding of prediction residuals

Signal modeling with non-uniform topology lattice filters

Contact Info

Product

Resources

About