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Split-dimension vector quantization of Parcor coefficients for low bit rate speech coding

机译:低比特率语音编码的Parcor系数的分维矢量量化

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摘要

A novel split vector quantization (SVQ) scheme for low bit rate coding of speech signals is proposed. In this scheme, the LPC parameter vector, which is represented by Parcor coefficients, is split into small-dimension subvectors, and each subvector is sequentially quantized according to a multistage structure that resembles a segmented lattice filter. The forward and backward prediction residuals in the segmented filter are coupled across VQ stages. The quantizer in each stage operates on the principle of minimizing the forward and backward prediction error energies similar to linear predictive analysis. Simulation results show that the new split VQ scheme can achieve transparent quantization of LPC parameters at 25 b/frame.
机译:针对语音信号的低比特率编码,提出了一种新颖的分离矢量量化(SVQ)方案。在该方案中,将由Parcor系数表示的LPC参数向量分解为小尺寸的子向量,并根据类似于分段晶格滤波器的多级结构对每个子向量进行顺序量化。分段滤波器中的前向和后向预测残差跨VQ级耦合。类似于线性预测分析,每个阶段中的量化器均根据使正向和反向预测误差能量最小化的原理进行操作。仿真结果表明,新的分离式VQ方案可以在25 b /帧的情况下实现LPC参数的透明量化。

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