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自相关虽然能够判断清/浊音,并估计浊音的基音周期,但是其运算量很大,用乘法运算所需时间较长。为了避免乘法,采用短时平均幅度差函数(AMDF),验证AMDF与自相关有类似的作用,即平均幅度差函数能够代替自相关函数进行语音分析。-Although autocorrelation can differ from the Voiced/Unvoiced and voiced the pitch period estimate, but the operation is large enough, with the multiplication time was needed. In order to avoid the multiplication using the short time average magnitude difference function (AMDF), verify the AMDF and autocorrelation have a similar effect, that the average magnitude difference function can replace the voice of the autocorrelation function.
Date : 2025-12-21 Size : 20kb User : 吴艳花

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 autocorrelation function, short-term magnitude difference, cepstrum, complex cepstrum, lpc coefficient, lpc absolute guarantee of the quality of spectral estimation, is the security arrangement of some of the research base after the mentor program
Date : 2025-12-21 Size : 6kb User : 林溪

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首先通过手机录制一段名为“yuyin.wav”的语音,然后通过MATLAB编写程序对这段语音进行分析,分别求出这段语音短时能量、短时过零率、短时幅度以及清音和浊音的自相关函数-First phone to record a section called " yuyin.wav" the voice, and then through the MATLAB programming analysis of this voice, this voice were calculated short-term energy, short-time zero-crossing rate, short-term rate and the voiceless and voiced the autocorrelation function
Date : 2025-12-21 Size : 1kb User : Colin

基于Matlab的语音信号的时域分析,包括短时平均能量,短时平均过零率,短时自相关系数,短时平均幅度-Based on Matlab speech signal time-domain analysis, including short-term average energy, short-time average zero-crossing rate, short-term autocorrelation coefficient, the short-term average
Date : 2025-12-21 Size : 3kb User : 海日水

采用MATLAB 2015b综合运用各种函数调用等来实现语音信号时域的短时能量,短时过零以及短时自相关函数分析和频域的傅里叶变换,功率谱估计,短时傅里叶变换,小波分析,语音信号的短时综合,语谱图各种分析,充分了解熟悉语音信号的相关分析方法。(This experiment uses the MATLAB 2015 b, the integrated use of various kinds of function call to realize speech signal in time domain of short-time energy and short-time zero crossing and short-time autocorrelation function analysis and frequency domain Fourier transform, power spectrum estimate, short-time Fourier transform, wavelet analysis, the short synthesis speech signal, the spectra of various analysis, fully understand the familiar voice signal correlation analysis method.)
Date : 2025-12-21 Size : 408kb User : Liu0_
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