语音信号处理赵力（中文入门）

这是自己毕业设计做的PCA和LDA的结合，训练和识别别过程都有，用的是ORL库里的图像，具有较高的识别率！ (This is a combination of PCA and LDA graduation design, training and do the process of the identification with ORL library of images, has a high recognition rate!)

一个完整的基于Matlab的DTW模型算法及高效算法程序，能快速识别数字0-9,运行testdtw即可。(An excellent MATLAB program for the algorithm as a DTW model. It can recognise the number of 0-9. Try it, just run testdtw.)

语音库开发工具源码，例程程序创建机读SAPI.SpVoice对象开发语音库。(Speech development tools source , routine program to create machine-readable SAPI.SpVoice speech object development .)

微软研究院的说话人识别工具包，包括GMM-UBM、I-Vector。其中demo_gmm_ubm_artificial.m和demo_ivector_plda_artificial.m为生成模拟特征参数进行训练与识别的教学示例，十分适合初学者学习说话人识别基础算法。具体使用方法请看内部文档。(Microsoft Research s speaker recognition toolkit, including GMM-UBM, I-Vector. Demo_gmm_ubm_artificial.m and demo_ivector_plda_artificial.m which generates an analog characteristic parameters for example teaching training and recognition, very suitable for beginners to learn the basic algorithm for speaker recognition. See the specific use of internal documents.)

一个LMS自适应信号增强。输入信号是一个正弦 波将白噪声。 详细介绍了程序源代码(An LMS adaptive signal enhancement. The input signal is a sine wave with added white noise. The detailed description is in the program source code)

一个可执行的HMM语音识别程序例程，实现了对10个数字音的识别程序，包含了HMM语音识别中的分段，MFCC特征提取，Baum-Welch训练，及Viterbi等算法，通过此例程可以很好的理解HMM的算法原理(An executable HMM-based 10 digits speech recogntion program example. this code zip file includes segmentation, MFCC feature extraction, Baum-Welch based re-estimation and Viterbi algorithm involved in HMM. it helps much better understand the HMM algorithm and its application for speech recogntion. )

实现语音的分割和识别，语音分割通过短时能量和过零率，语音识别通过dtw算法。(audio cut and reconige)

matlab程序，从语音中提取lpcc，可以修改维数，带详细中文解释，方便阅读。(matlab program, extracted from voice lpcc, you can modify the dimension, with a detailed explanation of the Chinese, and easy to read.)

C语言实现的端点检测,具有良好的效果,对于做语音识别者来说，是很好的参考(C language implementation of endpoint detection, with good results)

lms alghoiritm method adaptive system