We present a fixed rate encoding scheme for the line spectrum pair (LSP) representation of an LPC-filter, based on Gaussian mixture (GM) modeling. For each mixture component, we construct a codebook by a union of product quantizers. Each local codebook is trained, independently, using a clustering scheme similar to the generalized Lloyd algorithm (GLA), over synthetic data. The training algorithm iterates fast, due to low complexity encoding, and converges in few iterations. The overall codebook is a combination of local codebooks, and inherits their high performance, while having a moderate complexity. We provide numerical results for average spectral distortion (SD) of the proposed encoder, and benchmark them by a lower bound, according t...
Line Spectral Frequencies (LSF) provide an alternate parameterization of the analysis and synthesis ...
Source coding based on Gaussian Mixture Models (GMM) has been recently proposed for LPC quantization...
In this paper, we investigate the use of a Gaussian MixtureModel (GMM)-based quantizer for quantizat...
International audienceThe Line Spectrum Pairs (LSP) provide an efficient representation of the synth...
Includes bibliographical references (pages [109]-111)This thesis employs line spectral pairs (LSPs) ...
In this paper, we investigate the use of a Gaussian MixtureModel (GMM)-based quantizer for quantizat...
The Line Spectrum Pair (LSP) parameters have been established as one of the most efficient methods f...
This paper presents a method for obtaining numerical estimates of high rate vector quantization (VQ)...
The LSP speech analysis-synthesis method is known as one the most efficient vocoders. An important i...
This paper proposes a scalable speech coding scheme using the embedded matrix quantization of the LS...
In this paper, we investigate the use of a Gaussian MixtureModel (GMM)-based quantizer for quantizat...
International audienceThe line spectrum pairs (LSP) provide an efficient representation of the synth...
This paper proposes a scalable speech coding scheme using the embedded matrix quantization of the L...
Linear predictive coding (LPC) is employed in many low bit rate speech coders. LPC models the short-...
Abstruct- Linear predictive coding (LPC) parameters are widely used in various speech processing app...
Line Spectral Frequencies (LSF) provide an alternate parameterization of the analysis and synthesis ...
Source coding based on Gaussian Mixture Models (GMM) has been recently proposed for LPC quantization...
In this paper, we investigate the use of a Gaussian MixtureModel (GMM)-based quantizer for quantizat...
International audienceThe Line Spectrum Pairs (LSP) provide an efficient representation of the synth...
Includes bibliographical references (pages [109]-111)This thesis employs line spectral pairs (LSPs) ...
In this paper, we investigate the use of a Gaussian MixtureModel (GMM)-based quantizer for quantizat...
The Line Spectrum Pair (LSP) parameters have been established as one of the most efficient methods f...
This paper presents a method for obtaining numerical estimates of high rate vector quantization (VQ)...
The LSP speech analysis-synthesis method is known as one the most efficient vocoders. An important i...
This paper proposes a scalable speech coding scheme using the embedded matrix quantization of the LS...
In this paper, we investigate the use of a Gaussian MixtureModel (GMM)-based quantizer for quantizat...
International audienceThe line spectrum pairs (LSP) provide an efficient representation of the synth...
This paper proposes a scalable speech coding scheme using the embedded matrix quantization of the L...
Linear predictive coding (LPC) is employed in many low bit rate speech coders. LPC models the short-...
Abstruct- Linear predictive coding (LPC) parameters are widely used in various speech processing app...
Line Spectral Frequencies (LSF) provide an alternate parameterization of the analysis and synthesis ...
Source coding based on Gaussian Mixture Models (GMM) has been recently proposed for LPC quantization...
In this paper, we investigate the use of a Gaussian MixtureModel (GMM)-based quantizer for quantizat...