语音递归随机树编码

Hoontaek Oh, J. Gibson
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引用次数: 0

摘要

我们研究了一种基于树编码概念的递归自适应语音编码架构,结合递归最小二乘格估计的自回归分量和基于梯度的移动平均部分估计的短期预测和基于梯度/自相关的长期预测算法,所有这些都适应最小化感知加权重构误差。介绍并探讨了串联随机多树的新思想。语音活动检测(VAD)和舒适噪声产生(CNG),以减少比特率和所需的计算量。性能与广泛实现和使用的AMR编解码器进行了比较,我们在4.5到7.5 kbits/s的比特率下展示了相当的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recursive Randomized Tree Coding of Speech
We study a recursively adaptive architecture for speech coding based on the concept of tree coding combined with recursive least squares lattice estimation of the autoregressive component and gradient based estimation of the moving average part of the short term prediction and gradient/autocorrelation based long term prediction algorithms, all adapting to minimize the perceptually weighted reconstruction error. The new idea of concatenated, randomized multitrees is introduced and explored. Voice activity detection (VAD) and comfort noise generation (CNG) are included to reduce the bit rate and the number of computations required. Performance is compared to the widely implemented and utilized AMR codec and we demonstrate comparable performance at bit rates of 4.5 to 7.5 kbits/s.
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