论文标题
线性和非线性语音预测之间的比较研究
A comparative study between linear and nonlinear speech prediction
论文作者
论文摘要
本文的重点是非线性预测编码，该编码是基于先前样本的非线性组合的语音样本的预测。众所周知，在发光脉冲的生成中，波方程不会线性地表现[2]，[10]，并且我们通过基于参数神经网络模型的非线性预测语音预测来对这些效果进行建模。这项工作集中在神经净重的量化和压缩增益上。
This paper is focused on nonlinear prediction coding, which consists on the prediction of a speech sample based on a nonlinear combination of previous samples. It is known that in the generation of the glottal pulse, the wave equation does not behave linearly [2], [10], and we model these effects by means of a nonlinear prediction of speech based on a parametric neural network model. This work is centred on the neural net weight's quantization and on the compression gain.
