可以求出语音信号的LPC倒谱特征向量，该特征向量在语音信号分析中得到了广泛的应用。
Voice signal can be obtained by LPCCEP eigenvector, the eigenvector of the voice signal analysis has been widely used.
利用听觉频率非线性特性的美尔倒谱作为语音识别的特征参数，来辨识说话人提供的输入口令。
Also, since MFCC represent hearing frequency nonlinear characteristic, we utilize MFCC to be another speak recognition characteristic parameter to distinguish the input passwords.
将梅尔倒谱参数和线性预测参数结合起来作为语音识别的特征提取参数。
The MFCC coefficients and LPCC coefficients are combined as the speech recognition feature extraction parameters.
利用倒谱包络方法解决液压泵轴承故障特征提取和故障诊断的问题。
The cepstrum envelope analysis is applied to solve the problem of the diagnosis of bearing failure to hydraulic pump.
此外，本文应用这种方法提取语声倒谱的积谱、谱矩距离等语音时变特征，并加以伪彩色编码显示。
Moreover, the applications of this method to feature extraction of cepstrum product and spectral moment distance are described.
在概率模型中，给出了引入倒谱预测值的动态相关性来进行特征补偿的方法。
The paper introduces a new feature compensation method which will induct the relativity of the prediction of spectrum based probability model in detail.
在概率模型中，给出了引入倒谱预测值的动态相关性来进行特征补偿的方法。
The paper introduces a new feature compensation method which will induct the relativity of the prediction of spectrum based probability model in detail.
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