一种高效、低存储的线谱频率参数矢量量化器

    An Efficient LSF Parameters Quantizer With Low Storage

    • 摘要: 为了降低线谱频率(LSF)参数矢量量化器的搜索复杂度和码字存储单元,利用LSF参数的帧内和帧间相关性,设计了一种LSF参数的预测式多级分裂矢量量化器.该量化器对LSF参数的预测残差矢量进行两级矢量量化,其中第2级的误差矢量分裂成2个维数分别为4和6的子矢量进行矢量量化,采用瞬时联合多级矢量量化器设计算法设计码本,应用M-L树搜索算法搜索码字,降低了搜索复杂度和码字存储单元,在20 bit时,平均谱失真小于1 dB.

       

      Abstract: To reduce the computational complexity and storage of the line spectrum frequency(LSF) parameters quantizer a predictive multi-stage split vector quantizer is designed to quantize LSF parameters by using the correlation of LSF parameters between frames and inter frames. The LSF residual vector is quantized by 2-stage vector qutization (VQ) and error vector is divided into 4-D and 6-D subvectors in the second stage. This vector quantizer achieves an average spectral distortion of less than 1 dB at 20 bits/frame with low computational complexity and storage, where the mulit-stage VQ simultaneous joint design algorithm is used to train the codebooks and the M-Ltree search algorithm is applied to select codes.

       

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