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SPLIT VQ AND PREDICTIVE SPLIT VQ OF LSP PARAMETERS IN PACKET NETWORKS

机译:分组网络中LSP参数的拆分VQ和预测拆分VQ

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In many speech coding systems, the LPC coefficients are transformed to the Line Spectrum Pairs (LSP) parameters which are very effective representation for quantization of the LPC information. LSP representation consumes a large part of the total bit rate of the coder. Typically, the LSP are highly correlated from one frame to the next one, and a considerable reduction in bit rate can be achieved by exploiting this interframe correlation. However, interframe LSP coding can cause error propagation when frame erasures occur. In this paper, we compare the erasure performance of a predictive split vector quantizer to that of split vector quantizer based on the ITU G723.1 standard coder. Our results show that a 25 bits/frame split vector quantizer improves the average of spectral distortion of the 24 bits/frame predictive split vector quantizer based on The ITU G.723.1 for different loss rates.
机译:在许多语音编码系统中,LPC系数被变换为线谱对(LSP)参数,这是非常有效的表示LPC信息的表示。 LSP表示消耗了编码器总比特率的很大一部分。通常,LSP从一个帧与下一个帧高度相关,并且通过利用这种帧间相关性可以实现比特率的相当大降低。然而,当发生帧擦除时,帧间LSP编码会导致错误传播。在本文中,我们基于ITU G723.1标准编码器比较了预测拆分矢量量化器的擦除性能与拆分矢量量化器的擦除性能。我们的结果表明,基于ITU G.723.1的不同损失率,25位/帧分体式矢量量化器可提高24位/框架预测分离矢量量化器的光谱失真的平均值。

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