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基于LPC美尔倒谱特征的带噪语音端点检测
- 基于LPC美尔倒谱特征的带噪语音端点检测.rar格式为ｖｉｐ-America Fall Cepstral Noisy voice endpoint detection. Rar format vip
LPCC.rar
- 可以在CCS中运行的LPCC程序，包括语音参数分析主函数，信号的自相关函数，由自相关函数计算LPC预测系数，由LPC预测系数计算LPC倒谱系数，由LPC预测系数计算MEl到普系数等函数,CCS can be run at the LPCC procedures, including analysis of voice parameters of the main function, the signal autocorrelation function, autocorrelation func
lpc
- matlab 求线性倒谱系数,用于语音识别-matlab linear cepstral coefficients for speech recognition
2028
- OTOMATİ K KONUŞ MA TANIMA ALGORİ TMALARININ UYGULAMALARI Kö ksal Ö CAL Ankara Ü niversitesi Fen Bilimleri Enstitüsü Elektronik Mühendisliğ i Anabilim Dalı Danı ş man : Yrd. Doç . Dr. H. Gö kh
mfcc
- 提取LPC参数进行，倒谱系数的计算，用于静音检测算法，-Extract LPC parameters, the calculation of cepstral coefficients for mute detection algorithm
cepstrum_coeffi
- lpc to cepstral coefficient
LPCAUTO
- LPC倒谱系数提取，提取出来的LPC倒谱系数可以线性预测，帮助语音信号处理-LPC cepstral coefficients the number of extraction，Extracted from the LPC cepstrum coefficients linear prediction to help the speech signal processing
speech
- 包含语音端点检测，lpc倒谱系数，durbin算法，mel倒谱系数以及复倒谱系数。-Contains the speech endpoint detection, the lpc cepstrum coefficients, durbin algorithm, mel cepstral coefficients and the complex cepstrum coefficients.
other_features
- these are two audio features , LPC whith cepstral coefficients this a feature for speech recognition and speaker recognition , and other feature named zcr for calculate the change of the sing ( + or - ) of the signal.
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- these are two audio features , LPC whith cepstral coefficients this a feature for speech recognition and speaker recognition , and other feature named zcr for calculate the change of the sing ( + or - ) of the signal.
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- these are two audio features , LPC whith cepstral coefficients this a feature for speech recognition and speaker recognition , and other feature named zcr for calculate the change of the sing ( + or - ) of the signal.
lpc_vocoder_rev2
- 这个MATLAB构建一个锻炼LPC声码器,即,执行LPC分析和合成语音文件,导致合成语音近似原始的演讲。LPC分析使用一个标准的自相关分析来确定LPC系数的设置,一帧一帧的基础上,以及框架获得。一个独立的分析方法(cepstral螺距内检测器)把每一帧的言论是要么表示演讲(时间由cepstral峰值的位置在指定范围的音调时期)或无声的言论(模拟随机噪声帧)0帧基音周期的样本。独立的分析提供了一个两国并存的激发函数LPC合成处理的一部分,包括一系列的脉冲(表示帧期间)和/或噪声序列(在无声的帧)。