低比特率线谱对量化器及其在语音编码中的应用

R. El-Kouatly, S. El-Ramly
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引用次数: 1

摘要

本文提出了一种基于差分LSP技术和移动平均帧间预测相结合的高效线频谱对量化器。差分技术用于去除当前帧中相邻LSP系数之间的相关性,而移动平均(MA)预测用于去除连续帧中相应系数之间的相关性。残差量化采用两种技术,第一种是低复杂度标量量化器,每帧20-25位,帧大小为20 ms。第二种算法复杂度较高,但比特率较低,采用每帧14比特的两级矢量量化器(VQ)。DMAP量化技术的性能可与ITU-T G.729标准中使用的移动平均两级分裂矢量量化器相媲美。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Low bit rate line spectrum pair (LSP) quantizer with application to speech coding
This paper proposes a new efficient line spectrum pair (LSP) quantizer, which is based on the combination of the difference LSP techniques and moving average (MA) interframe prediction. The difference technique is used to remove the correlation between adjacent LSP coefficients in the present frame, while the moving average (MA) prediction removes the correlation between the corresponding coefficients in successive frames. Two techniques are used for residual quantization, the first is a low complexity scalar quantizer with 20-25 bits per frame with 20 ms frame size. The second is of higher complexity but lower bit rate which uses 14 bits per frame two stages vector quantizer (VQ). The DMAP quantization technique yields a good performance comparable to the moving average two-stage split vector quantizer used in the ITU-T G.729 standard.
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