Title | ||
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Low-complexity wideband LSF quantization by predictive KLT coding and generalized Gaussian modeling |
Abstract | ||
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In this paper we present a new model-based coding method to rep- resent the linear-predictive coding (LPC) parameters of wideband speech signals (sampled at 16 kHz). The LPC coefficients are transformed into line spectrum frequencies (LSF) and quantized by switched AR(1)/MA(1) predictive Karhunen-Loeve transform (KLT) coding. Compared to previous work, the main novelty lies in the use of improved quantization to represent the (transformed) prediction error of LSF parameters. Generalized Gaussian model- ing is applied for this purpose. We review existing methods to fit the free model parameter of a generalized Gaussian model to real data and show that that the distribution of the prediction error for LSF parameters is indeed very close to Laplacian. Experimental results show that the proposed LSF quantization method has a performance close to classical vector quantization (AMR-WB LPC quantization) at 36 and 46 bits per frame with a much lower complexity for both design and operation. |
Year | Venue | Keywords |
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2006 | EUSIPCO | gaussian distribution,karhunen-loeve transforms,linear codes,quantisation (signal),speech processing,amr-wb lpc quantization,karhunen-loeve transform,lsf parameters,classical vector quantization,frequency 16 khz,generalized gaussian modeling,line spectrum frequency,linear-predictive coding,low-complexity wideband lsf quantization,prediction error,predictive klt coding,wideband speech signals |
Field | DocType | ISSN |
Wideband,Wideband audio,Pattern recognition,Coding (social sciences),Vector quantization,Gaussian,Quantization (physics),Gaussian network model,Artificial intelligence,Quantization (signal processing),Mathematics | Conference | 2219-5491 |
Citations | PageRank | References |
3 | 0.49 | 8 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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marie oger | 1 | 12 | 2.82 |
stephane ragot | 2 | 30 | 4.98 |
Marc Antonini | 3 | 50 | 3.71 |