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2LMSE最小均方误差算法
- 模式识别中关于 LMSE最小均方误差算法 一中算法-pattern recognition on the wan minimum mean square error algorithm an algorithm
MMSE_IC
- 基于LMS(最小均方误差算法)的自适应滤波 基于LMS(最小均方误差算法)的自适应滤波-based on the LMS (MMSE) algorithm based on the LMS adaptive filtering (minimum mean square error algorithm) the adaptive filtering based on the LMS (minimum mean square error algorithm) Adaptive Filter
DETware_v2[1].1.tar
- 求误识率——拒识率曲线（DET曲线） 常应用于说话人识别-seek error rate -- reject rate curve (DET curve) often used in speaker recognition
det(C++)
- 计算误识率——拒识率曲线（VC++） 应用于说话人识别系统中。-calculation error rate -- reject rate curve (VC) for speaker recognition system.
LSAgai
- 对数谱最小均方误差语音增强算法（LSA-MMSE），对加入有音无音判决进一步提高信噪比，消噪效果非常好。适合各种平稳噪声。-right spectrum minimum mean square error speech enhancement algorithm (LSA - MMSE). sound right to a sound judgment without further improve signal-to-noise ratio, denoising effect was very
equ
- LMS算法的训练滤波器，均衡滤波处理，硬判决，包括：1训练，2均衡处理，3判决并计算误码-training filter, filter balanced, hard decision, including : a training and two balanced, 3 judgment and calculation error
lms
- 再传一个LMS的小程序，有三个图，System output，Error curve，Comparison of the actual weights and the estimated weights
eqber_adaptive
- This scr ipt runs a simulation loop for either a linear or a DFE equalizer. It uses the RLS algorithm to initially set the weights, then uses LMS thereafter to minimize execution time. It plots the equalized signal spectrum, then generates and plot
chapter6_1
- 用自相关法求使信号s均方预测误差为最小的预测系数 算法为Levinson-Durbin快速递推算法 -Method using the signal from the associated mean square prediction error s for the smallest prediction coefficient algorithm Levinson-Durbin recursive algorithm for fast
LPC
- 基于线性预测系数(LPC)的语音信号重构。给出了完整的LPC matlab程序，包括语音信号采集，LP预测系数，阶数的选择以及预测结果误差曲线。（很好用）-Based on the linear prediction coefficient (LPC) voice signal reconstruction. Given a complete LPC matlab procedures, including voice signal acquisition, LP prediction coef
speech-enhancement
- 本资料涵盖了几乎所有的语音增强方面的方法，主要有谱减法，听觉掩蔽，最小均方误差，维纳滤波以及一些非主流的方法，这些对于研究语音增强的人来说是很有帮助的-The data cover almost all aspects of speech enhancement methods, the main spectral subtraction, auditory masking, minimum mean square error, Wiener filtering as well as some
1
- LMS 算法源程序，绘制性能曲线图，误差性能曲线-LMS algorithm source code, rendering the performance curves, the error performance curve
yinacf10
- The Yin algorithm was developed by Alain de Cheveigné of IRCAM-CNRS and Hideki Kawahara of Wakayama University. It allows for real-time continuous (for each sample) fundamental frequency estimation. It features a very low error rate and few tuni
emd
- 这个程序使用来对语音信号进行端点效应处理，以减小端点效应对信号带来的误差。、-This process used to signal the endpoint of the voice effect processing, to reduce the effect of endpoint error signal. ,
pattenrecongition
- 通过用最小距离分类判别方法，用MATLAB程序找出最小距离分类判别时的识别界面，从而进行识别已知的两类训练样本，并分析其识别错误率。-By using minimum distance classifier discriminant method, using MATLAB program to find the minimum distance classifier recognition interface when the judge, which is known to identify
Unsupervised_Adapting_in_Speech_Recognising_using_
- 介绍了一种基于词网的最大似然线性回归无监督自适应算法，并进行了改进。根据解码得到的词网估计变换参数，词网的潜在误识率远小于识别结果，因此可以使参数估计更为准确。传统的一个很大缺点是计算量极大，较难实用，对此本文提出了两个改进技术：1利用后验概率压缩词网；2利用单词的时间信息限制状态统计量的计算范围。实验测定,误识率比传统相对下降了。-Introduced the term network based maximum likelihood linear regression unsupervise
Spedaker_Adapting_in_Speech_recognizing
- ：自适应技术在近年来得到越来越多的重视，其中应用广泛的包括,-.、,//0，该技术利用少量特定 人数据就可以调整码本，快速地提升识别性能，它要求原始的码本有很好的说话人无关性。本文介绍了结合 ,//0 自适应的说话人自适应训练（1234536 -74289:3 649<9<=，以下简称1- ）算法，这种方法将每个说话人码本 视为说话人无关码本经过线性变换的结果，在此基础上训练的说话人无关码本更有效剔除了说话人相关信 息，因此在说话人自适应中时能根据特定数据调整更好地逼
mic1
- There are four major types of adaptive filtering configurations adaptive system identification, adaptive noise cancellation, adaptive linear prediction, and adaptive inverse system. All of the above systems are similar in the implementation of the al
real-time-voice-prompts
- 如果你经常输入汉字或数字，那你肯定会对这个软件感兴趣——即时语音提示／校对专家。 即时语音提示／校对专家是一款语音识别和语音合成软件，能在你键盘输入的同时把你所输入的字符或汉字读出来，这样就可以大幅度提高工作效率了，这点对于用五笔或其它形码的朋友来说就更显得意义重大了，它能避免汉字输入过程中很多最常犯的错误和许多稀奇古怪、莫名其妙的错误。-If you often enter characters or numbers, then you will certainly be interes
voice-recognition_matlab-code
- 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 paramet