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首页> 外文期刊>Radioengineering >Forward Adaptive Dual-Mode Quantizer Based on the First-Degree Spline Approximation and Embedded G.711 Codec
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Forward Adaptive Dual-Mode Quantizer Based on the First-Degree Spline Approximation and Embedded G.711 Codec

机译:基于第一度样条近似和嵌入式G.711编解码器的转发自适应双模量化器

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In this paper, we propose a novel model of dual-mode quantizer that combines the restricted and unrestricted forward adaptive piecewise linear scalar quantizers based on the first degree-spline functions, one of them being forward adaptive G.711 quantizer used as the unrestricted one. The analysis presented in the paper can be considered as our further research in the field of dual-mode quantization. In particular, in our novel model we utilize G.711 codec due to the compatibility reasons and we develop one completely novel model of restricted quantizer based on the first-degree spline approximation, which is optimized for the assumed Laplacian source so that to provide a minimal mean-squared error distortion. Moreover, unlike previous dual-model quantizer models that processed signals in frame-by-frame manner, our novel model utilizes frame/subframe processing of the signal in order to decrease the total bit rate. The theoretical analysis in a wide dynamic range of input signal variances reveals that the proposed model of quantizer is superior versus the unrestricted G.711 quantizer as well as other similar baselines having the same number of quantization levels. In addition, the results of the experimental analysis performed on the real speech signal show a good agreement with the theoretical ones.
机译:在本文中,我们提出了一种新颖的双模量化模型,该模型基于第一度样条函数结合了限制和不受限制的自适应分段线性标量化器,其中一个是向前的自适应G.711量化器作为不受限制的。本文提出的分析可以被认为是我们在双模量化领域的进一步研究。特别地,在我们的小说模型中,我们利用G.711编解码器由于兼容性原因,并且我们基于第一度样条近似开发了一个完全新颖的限制量化模型,这针对假定的拉普拉斯源进行了优化,以便提供a最小的平均误差失真。此外,与先前的双模型量化器模型不同,以逐帧方式处理信号,我们的新模型利用信号的帧/子帧处理以减小总比特率。在宽动态输入信号方差范围内的理论分析揭示了所提出的量化模型与不受限制的G.711量化器以及具有相同数量的量化水平的其他相似基线。此外,对真实语音信号进行的实验分析的结果表现出与理论上的良好协议。

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