搜索资源列表
yuyinshibie
- 语音信号的时频特性 语音信号的产生模型 语音信号的短时分析技术 语音信号线性预测分析 语音识别-Time-frequency characteristics of speech signal generation model of speech signal short-time speech signal analysis of linear prediction analysis of speech signals speech recognition
Multiplelinearregressonanalysisprediction
- 多元线性回归分析预测法针对概率论中的回归预测做了研究，推荐各位大侠阅读-Multiple linear regression analysis prediction for the probability of regression to do the research, recommended reading you heroes
project2
- 线性预测法是语音处理中的核心技术，它在语音识别、合成、编码、说话人识别等方面都得到了成功应用。有的专家认为，进20年中语音处理技术的飞速发展与以线性预测为中心的信号处理技术是分不开的。简单来说，就是：一个语音的抽样能用过去若干语音抽样的线性组合来逼近。 -Linear prediction is the core voice processing technology, which in speech recognition, synthesis, coding, speaker recog
LPC
- FUNDAMENTALS OF LINEAR PREDICTION
xianxingyuce
- 阵列信号，16阵元，3信源的线阵条件下的线性预测算法-Array signal, 16 array, 3 sources of linear conditions, the linear prediction algorithm
chapter2-low-bit-rate-speech-coding
- Chapter 2 Low Bit-Rate Speech Coding In this chapter an overview is given of speech coding techniques at several bit rates. Most of them use Linear Prediction. This overview is not meant to be complete its purpose is to make the reader somewhat
ymx
- 线性预测分析是现代语音信号处理中最核心的技术之一，为现代语音信号处理的飞速发展立下了赫赫功劳，在语音分析、合成、编码、识别等方面都有着广泛的应用，至今仍是最有效的语音分析技术之一。-Linear prediction analysis is the most modern speech signal processing one of the core technology for the modern rapid development of voice signal processing a
yuceqi
- 分别采用维纳滤波和l-d算法设计一个6阶前向线性预测器，给出设计过程，matlab程序。 要求：1、得到预测器的权向量和预测误差功率 2、画出预测阶数和预测误差功率的曲线 3、在使用l-d算法时，假设 ， ，…… 未知 -Wiener filter and were used to design a 6-ld algorithm prior to the linear predictor order, given the design process, matlab prog
step_linear_predetict_and_Weiner_filter
- 一步线性预测与Weiner滤波的比较，含GUI界面.-Step linear prediction compared with the Weiner filter, with GUI interface.
FS
- 采用局部线性逼近法来预测复杂的混沌时间序列。-Local linear approximation method using chaotic time series prediction
hundun
- 这是有关非线性在语音预测编码、识别等方面的应用，还有神经网络方法在语音预测编码、语音增强、识别等方面的应用，相当有用哦！-This is the non-linear prediction in speech coding, recognition and other applications, as well as neural network prediction in speech coding, speech enhancement, recognition and other appl
LinPF
- This a VHDL module that implements linear prediction filter based on NLMS (normalized least mean square). The module takes complex signal as input and output comlex signal (real and imaginary). Tap size is 4, bit precision is set to 12 bits.-This i
LinPF_RLS
- VHDL code for linear prediction filter based on RLS (recursive least square). Filter order is set to 4, bit precision set to 12 bits for input and output. Signals are complex signals.
Assignment2
- 国外高校老师编写的语音信号特征提取程序，非常实用初学者研究- [E, V, A, P] = analysis(x, N, U, M) extracts vocoder parameters E, V, A, and P from the speech signal x on a frame by frame basis. N is the analysis frame length, U is the update length, and M is the order of the
NumericalRecipesinCWilliam.H
- 本书编写了300多个实用而有效的数值算法C语言程序。其内容包括：线性方程组的求解，逆矩阵和行列式计算，多项式和有理函数的内插与外推，函数的积分和估值，特殊函数的数值计算，随机数的产生，非线性方程求解，傅里叶变换和FFT，谱分析和小波变换，统计描述和数据建模，常微分方程和偏微分方程求解，线性预测和线性预测编码，数字滤波，格雷码和算术码等。全书内容丰富，层次分明，是一本不可多得的有关数值计算的C语言程序大全。本书每章中都论述了有关专题的数学分析、算法的讨论与比较，以及算法实施的技巧，并给出了标准C语
qqcelp
- QCELP是美国Qualcomm通信公司的专利语音编码算法，是北美第二代数字移动电话的语音编码标准（IS-95）。QCELP算法被认为是到目前为止效率最高的一种算法。该算法可依靠门限值来调整速率，门限值随着背景噪声的变化而变化-Qualcomm Code Excited Linear Prediction
dip3
- 设计了三个帧内线性预测的算法，给出原始图像及其直方图并给出了预测误差图等-Designed three frame linear prediction algorithm, given the original image and its histogram and gives the prediction error map, etc.
dtw
- 本系统是一个在多媒体PC 上实现的孤立词识别系统, 它提取语音的线性预测系数作为特征参数, 并采用Itaku ra 失真测度计算帧间距离, 在识别上则使用了动态时轴弯曲(DTW ) 进行时间匹配。本系统对一般的DTW 法作了改进, 即通过放宽端点限制以得到更好的语音匹配, 克服了一般DTW 法要求语音首尾严格对齐而造成的弊病, 降低了语音端点检测的精度要求。-This system is implemented on a multimedia PC isolated word recogniti
duandianjiance
- First to be discussed within the paper are general linear time-invariant systems, along with its theory and mathematics, before moving into a general descr iption of linear prediction models
voicebox
- A section focussing specifically on the linear prediction of speech then begins. The anatomical process of speech production is described, followed by an introduction to a theoretical linear model of the proce-A section focussing specifically on