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0下载：
语音参数短时能量，短时过零率，短时平均幅度，语音端点检测，fft变换与反变换-Voice parameters of short-time energy, short-time zero-crossing rate, short-term average rate, voice activity detection, fft transform and inverse transform
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利用短时平均能量和短时平均过零率，对语音信号进行端点检测-Average energy use of short-term and short-time average zero-crossing rate, speech endpoint detection signal
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时域波形、短时能量、短时平均幅度、短时过零率、短时过电平率-Time-domain waveform, short-term energy, short-term average rate, short-term zero crossing rate, short-term rates over Level
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基于MATLAB用于检测提取的语音信号的平均短时过零率的算法，可以方便的检测出是清音还是浊音。-Algorithm based on the MATLAB for detecting extracted speech signal average short-term zero-crossing rate, you can easily detect the voiceless or voiced.
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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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语音信号的时域、频域与倒谱域分析。
1.分析一帧清音和浊音的自相关函数和倒谱系数
2.用Matlab画出该段语音的时域波形、短时能量、短时平均幅度、短时过零率、短时过电平率
3.选择一帧无声、清音和浊音的语音，用Matlab画出它们的对数幅度谱(Time domain, frequency domain and cepstrum domain analysis of speech signals.
1. Analyze the autocorrelation function and c
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