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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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个人编写的提取音频信号的时域特征参数短时平均过零率及短时平均能量的matlab源程序。供大家参考-Extraction of individual preparation of the audio signal in time domain characteristic parameters of short-term average of zero-crossing rate and short-time average energy of the matlab source. For you
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：该文首先研究了单认知用户能量检测算法的检测性能和检测灵敏度与检测时长和噪声短时间内平均功率波
动性之间的关系，得出检测性能和检测灵敏度随噪声短时间内平均功率波动性的增大而急剧下降的结论，在低信噪
比时尤为明显；针对检测性能和检测灵敏度随噪声短时间内平均功率波动性的增大而急剧下降，提出了基于多用户
协同能量检测算法。-In this paper，detection performance and detection sensitivity with detection duratio
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编制LBG算法程序，以语音信号的短时平均能量为例，训练一个5比特码书，并给出量化器的失真特性。-Procedures for the preparation of LBG algorithm to short-time average energy of speech signals, for example, training for a 5-bit code book, and gives quantizer distortion characteristics.
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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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可进行短时平均能量，短时平均幅度，短时平均过零率，短时自相光，短时傅里叶变换的函数,使用方便，-The average energy can be short-term, short-term average rate, the average short-term zero-crossing rate, short-term autocorrelation of light, short-time Fourier transform of the function, easy to use,
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完成对一段语音信号的短时分析，语音信号要包括清音、浊音和无声段，求其短时平均能量、短时平均过零率、短时自相关函数和短时功率谱；-Complete short-term analysis of a voice signal, the specific requirements: a voice signal to include the voiceless, voiced, and silent segments 2, find its short-term average energy, sh
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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-Short-time speech signal analysis, mainly including: sub-frame, short-time energy, short-term average, short-time zero-crossing rate, short-time auto-correlation function, short-t
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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
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语音信号处理，含短时平均过零率、短时平均能量和短时平均幅度等的求解.
-Speech signal processing, including short-time average zero-crossing rate, short-term average energy and short-term average of solving.
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用短时平均能量值对干净的语音信号进行检测，可以区分语音和非语音部分-With short time average energy value to test the clean speech signal, can distinguish between voice and non-voice part
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训练语音和静音状态下短时平均能量的高斯模型，再通过统计方法来判断信号是语音还是静音-Training of voice and mute state gaussian model of short time average energy, again through the statistical method to determine the signal is a voice or a mute
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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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1.短时能量2．短时平均过零率3、短时自相关函数4.基音周期-1. The short-term energy 2. 3 short-time average zero-crossing rate, short-term autocorrelation function 4. Pitch
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本压缩包是对语音信号的短时分析，包含短时能量、短时过零率、短时自相关以及短时平均幅度差等函数-The compressed package is a short-term analysis of the speech signal, comprising short-time energy, short-term zero-crossing rate, short-term as well as short-time average magnitude of the autocorrelatio
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（1）理解矢量量化的基本原理。
（2）掌握矢量量化器设计的LBG方法。
（3）运用LBG方法获取语音短时平均能量码书-(1) to understand the basic principles of vector quantization.
(2) master the vector quantizer design LBG method.
(3) Using the LBG method to obtain the speech short time average ener
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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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在窗长为80和160个样点的情况下，分别采用矩形窗和哈明窗编程计算该段语音信号的短时平均能量，绘出短时平均能量曲线，并进行观察和比较(the window length is 80 and 160 sample points, short time average energy respectively using rectangular window and Hamming window programming calculation of the speech signal, short-t
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