Description: 该函数（线性预测）主要应用于声音处理与分析，在说话人识别中有着广泛的应用！-the function (Linear Prediction) will be used in voice processing and analysis, in the words of Recognition has wide application! Platform: |
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Author:张开 |
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Description: 实现LPC线性预测分析,能够提取AR模型参数并进行DCT变换处理-The realization of LPC linear prediction analysis, AR model parameters can be extracted and DCT transform Platform: |
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Author:miracomtrue |
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Description: lpc 线性预测分析 可以计算不同帧位和阶数的语音线性预测结果和误差-lpc linear prediction analysis, we can calculate the order of the different frames of voice-bit and Linear Prediction results and error Platform: |
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Author:mww |
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Description: Levison-Durbin 语音信号处理中的线性预测编码LPC 理论、格型滤波器以及求解现行预
测方程的算法，可以实现对语音信号重要元素的分析、合成甚至识别。
基于现有的实验平台，我们可以利用 Matlab 函数来获得几个固定语音元素（如元音）
的模型系数，LPC 得到的系数组成 IIR 滤波器。利用冲击脉冲
序列作为输入，我们就可以得到原来的语音。这是一种简单的语音合成功能。-Levison-Durbin speech signal processing in linear predictive coding LPC theory, lattice filters, as well as the current prediction equation solving algorithm, can achieve an important element of the speech signal analysis, synthesis or recognition. Based on the existing experimental platform, we can use Matlab function to obtain the number of fixed-voice elements (such as vowels) model coefficients, LPC coefficients are the composition of IIR filters. Shock pulse sequence used as input, we can get the original voice. This is a simple voice synthesis. Platform: |
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Author:Ender Lee |
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Description: 基于matlab的lpc分析，即线性预测。分析较为全面，且测试通过。-The lpc matlab-based analysis, that is linear prediction. More comprehensive analysis and test.
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Description: matlab中基于LPC线性预测分析处理语音的程序，用于对语音进行预测并与原语音作出比较
-matlab linear prediction based on LPC speech analysis and processing procedures for the prediction of speech to compare with the original voice Platform: |
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Author:marui |
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Description: 读入语音文件，并对其做时域、频域的分析，提取相关特征参数。进行线性预测分析，得到LPC谱等线性预测参数，并做了基于预测误差的基音周期估计。-read .wav files，analysing them in time domain，frequency domain and extract some feature parameters related，then do linear prediction analysis ，and get LPC linear prediction parameters，and fundamental tone period was estimated based on prediction error。 Platform: |
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Author:张婷婷 |
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Description: 线性预测分析是最有效的语音分析技术之一，在语音编码、语音合成、语音识别和说话
人识别等语音处理领域中得到了广泛的应用。语音线性预测的基本思想是：一个语音信号的
抽样值可以用过去若干个取样值的线性组合来逼近。通过使实际语音抽样值与线性预测抽样
值的均方误差达到最小，可以确定唯一的一组线性预测系数。-Linear predictive analysis is one of the most effective voice analysis technology has been widely applied in the field of speech processing speech coding, speech synthesis, speech recognition and speaker recognition and the like. The basic idea of linear prediction of speech is: a voice signal sample values can be approximated by a linear combination of a plurality of sample values of the past. By making the actual speech sample mean square error of the value of the smallest linear prediction sample values, to determine a unique set of linear prediction coefficients. Platform: |
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Author:tabob |
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Description: 本程序利用MATLAB对信号进行分析和处理，主要就是进行语音线性预测通过使实际语音抽样值与线性预测抽样值的均方误差达到最小，可以确定唯一的一组线性预测系数。-This procedure using MATLAB for signal analysis and processing, mainly for voice linear prediction by the actual voice sampling error of the mean square value and the minimum value of the linear prediction sample can be determined only one set of linear prediction coefficients. Platform: |
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Author:林霞 |
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Description: 首先对输入音频PCM信号进行时频分析，决定MDCT的长度，即加窗，然后进行MDCT变换；同时对原始音频信号要进行FFT分析。两种变换的频谱系输入给心理声学模型单元，MDCT系数用于噪声掩蔽计算，H可结果用于音调掩蔽特性计算，共同构造总的掩蔽曲线。然后根据MDCT系数及掩蔽曲线，对频谱系数进行线性预测分析用LPC(Linear Prediction Coefficience，线性预测系数)表示频谱包络，即基底曲线(Floor Curve)；或通过线性分段逼近方式获得基底曲线。从MDCT系数中去掉频谱包络则得到白化的残差频谱(Residue)，由于残差频谱波动范围明显变小，从而降低量化误差。之后可以选择是否采用声道耦合(Channel Coupling)技术进一步降低冗余度，耦合主要是将左右声道数据从直角坐标映射到平方极坐标；最后对白化的残差信号有效地以矢量量化表示。最后将要传输的各种信息数据按Vorbis定义的包格式组装，形成Vorbis压缩码流。-First, the input audio PCM signal time-frequency analysis to determine the length of the MDCT, that windowing, then MDCT transform while the original audio signal to FFT analysis. Two Transformations spectral line input to the psychoacoustic model unit, MDCT coefficients used to calculate the noise masking, H can be used to tone masking characteristic calculation result, the overall structure of the common masking curve. Then according to the MDCT coefficient and the masking curve, spectrum analysis using linear prediction coefficients LPC (Linear Prediction Coefficience, linear prediction coefficients) represent the spectral envelope, ie the base curve (Floor Curve) or approaching the base curve obtained by linear segments. Removed the MDCT coefficients in the spectral envelope of the residual spectrum obtained albino (Residue), since the fluctuation range of the residual spectrum significantly smaller, thereby reducing the quantization error. Then you can choose whether to use cha Platform: |
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Author:张小 |
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Description: 对一个元音和一个清辅音进行线性预测分析。LPC系数要分别有5阶，15阶和50阶三种情况，在同一坐标图里用不同颜色分别给出对应的LPC包络谱和FFT频谱，并试着对比分析。-A linear prediction of a vowel and a clear consonant. LPC coefficients should be 5 order, 15 and 50 order three cases, in the same coordinate map with different colors were given the corresponding LPC envelope spectrum and FFT spectrum, and try to compare the analysis. Platform: |
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Author:李紫净 |
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