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引用次数: 4

摘要

线性预测编码(LPC)滤波器系数的有效量化在极低比特率语音编码系统中起着至关重要的作用。本文研究了LPC参数的一种新的次优矩阵量化方案,称为多级矩阵量化(MSMQ),它的比特率在400到800比特/秒之间。采用新的矩阵量化方法,使用22.5 ms LPC分析帧,在800 bit/s下实现了约1 dB的频谱失真。该编码器将多个连续帧的线谱频率(LSF)参数组合成一个超帧并进行联合量化。新的残差LSF矢量量化方案在不增加复杂性和存储空间的情况下降低了MSMQ的比特率。新的MSMQ导致了几种不同计算复杂度/存储特性的方案。
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Multi stage matrix quantization for very low bit rate speech coding
Efficient quantization of linear predictive coding (LPC) filter coefficients play an essential role in very-low-bit-rate speech coding systems. This paper examines a new suboptimal matrix quantization scheme for LPC parameters, called multi-stage matrix quantization (MSMQ), which operates at bit rates between 400 and 800 bit/s. With the new matrix quantization method, using a 22.5 ms LPC analysis frame, spectral distortion about 1 dB is achieved at 800 bit/s. In the proposed coder, line spectral frequency (LSF) parameters of multiple consecutive frames are grouped into a superframe and jointly quantized. The new residual LSF vector quantization scheme gives a bit rate reduction in MSMQ without any additional complexity or storage. The new MSMQ leads into several schemes of various computational complexity/storage characteristics.
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