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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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