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this programme shows that how to calculate the autocorrelation and lpc coeffecients of a speech signal-this programme shows that how to calculate the autocorrelation and lpc coeffecients of a speech signal..
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linear prediction code is well known for speech coding method. this program use autocorrelation method for computing coefficient.-linear prediction code is well known for speech coding method. this program use autocorrelation method for computing coe
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lpc autocorrelation prediction for speech
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详细说明：语音信号的短时分析，主要包括：分帧、短时能量、短时平均幅度、短时过零率、短时自相关函数、短时幅度差、倒谱、复倒谱、lpc系数、lpc谱估计等 绝对保证质量，是保研后导师布置的一些基础程序-Details: short-time speech signal analysis, including: framing, short-term energy, short-term average rate, short-time zero crossing rate, short-time a
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用自相关法求使信号s均方预测误差为最小的预测系数 -Autocorrelation and the signal s mean square prediction error for the smallest prediction coefficients
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1.用matlab实现对一个元音和一个清辅音的LPC系数，LPCC系数和MFCC系数的提取。
2，用LPC对这两个语音信号的功率谱进行估计，其中，LPC系数要分别有5阶，10阶，15阶和20阶四种情况，并在一个图里画出信号本身的FFT功率谱和四条不同阶数的LPC谱估计图，以作比较。注意，LPC和LPCC只考察自相关法。
3，用对数面积比的方法来求出这两个发音的变截面声管模拟图形，10阶即可-Using matlab to achieve the LPC coefficients of a
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语音信号的线性预测（LPC）方程的自相关解法及其matlab实现。-Speech signal linear prediction (LPC) the autocorrelation Solution of the equation matlab.
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This MATLAB exercise designs and implements a pitch period detector based on detecting and tracking peaks in the autocorrelation of the LPC error signal during regions of voiced speech. The pitch detection procedure is called the SIFT (Simple Inverse
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本程序是用matlab编写的LPC算法，用于语音基频信号检测中。具体包括利用自相关法计算LPC系数。-This program is prepared using matlab LPC algorithm for speech baseband signal detection. Specifically including the use of LPC coefficients calculated autocorrelation method.
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这个MATLAB构建一个锻炼LPC声码器,即,执行LPC分析和合成语音文件,导致合成语音近似原始的演讲。LPC分析使用一个标准的自相关分析来确定LPC系数的设置,一帧一帧的基础上,以及框架获得。一个独立的分析方法(cepstral螺距内检测器)把每一帧的言论是要么表示演讲(时间由cepstral峰值的位置在指定范围的音调时期)或无声的言论(模拟随机噪声帧)0帧基音周期的样本。独立的分析提供了一个两国并存的激发函数LPC合成处理的一部分,包括一系列的脉冲(表示帧期间)和/或噪声序列(在无声的帧)。
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This MATLAB exercise computes the log magnitude of the STFT of a specified frame of speech. Then, using the
same frame of speech, the exercise computes LPC log spectral matches to the speech frame, using the autocorrelation
method, the covariance
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matlab编写,语音处理中求LPC系数的自相关程序,-In matlab, and speech processing for LPC coefficients autocorrelation procedure,
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matlab编写,语音处理中求LPC系数的自相关程序,-In matlab, and speech processing for LPC coefficients autocorrelation procedure,
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matlab编写,语音处理中求LPC系数的自相关程序,(In matlab, and speech processing for LPC coefficients autocorrelation procedure,)
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语音信号的短时分析，主要包括：分帧、短时能量、短时平均幅度、短时过零率、短时自相关函数、短时幅度差、倒谱、复倒谱、lpc系数、lpc谱估计等(The short-time analysis of speech signal mainly includes: frame, short-time energy, short time average amplitude, short-time zero crossing rate, short-time autocorrelation functio
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