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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, wit
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短时平均能量和平均幅度差函数进行基音检测的方法-Short-term average energy and average magnitude difference function pitch detection method
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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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循环AMDF及其语音基音周期估计算法 关键词： 平均幅度差函数；循环平均幅度差函数；基音周期估计-Circulating the AMDF its voice pitch estimation algorithm Keywords: average magnitude difference function cycle average magnitude difference function pitch estimation
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运用平均幅度差函数AMDF与Viterbi算法的后处理算算法提取语音基音周期一个程序源码，效果还不错 可直接使用。
-The use of the average magnitude difference function AMDF and the Viterbi algorithm, processing count algorithm to extract the voice pitch of a program source code, the results were pretty
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语音信号的时域、频域分析,包括短时能量分析、短时平均过零率、自相关函数、短时平均幅度差函数等。-Time-domain speech signal, frequency domain analysis, including short-term energy analysis, the average short-term zero-crossing rate, autocorrelation function, such as short-time average magnitude diff
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语音识别前期处理代码，包括语音信号预处理，预加重，加窗分帧，短时能量及短时平均幅度分析，短时平均过零率，短时自相关分析，短时平均幅度差函数。-Speech recognition pre-processing code, including voice signal pre-processing, pre-emphasis, windowing sub-frame, and the short-term average short-term energy analysis, the averag
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AMDF (average magnitude difference function)
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基于matlab的基音周期检测，自相关函数法和平均幅度差函数法-Matlab-based pitch detection, auto-correlation function and the average magnitude difference function method
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采用自相关函数法和平均幅度差函数法以及改进的平均幅度差函数法求一段音频的基音-Using the correlation function method and average magnitude difference function method and improved average magnitude difference function method for an audio pitch
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