好多朋友反映不太完善，比如：没有获取验证后倒计时的功能，没有加图片验证等。所以做了一些改进，希望大家可以参考一下。
以上例子，实现了如下功能：
1.获取验证码后倒计时的功能，可以自由设置
2。短信验证码的发送.
3.语音验证码的播报。
4。为了避免恶意获取，还加了图片验证码，再获取验证码的功能
A lot of friends reflect is not perfect, such as: no access to verify the countdown function, no image verification, etc.. So made a number of improvements, I hope you can refer to.
The following functions are realized:
1 to obtain verification code after the countdown function, you can set free
2. SMS verification code is sent.
3 voice verification code broadcast.
4. In order to avoid malicious access, but also add a picture verification code, and then get the verification code function (2015-12-10, ASP, 72KB, 下载1次)
pcm编码们以话音信号为例来说明数字通信的基本原理。人类的语音信号的频率范围在300—3 400 Hz之间，留有一定余地，设话音信号最高频率为4 kHz，则根据奈奎斯特采样定理，将话音信号数字化所需要的采样频率为8 kHz，即采样周期为l25 US 0再把每个采样值用8位二进制数字编码，就把模拟话音信号转换成了数字信号。因此，一路话音信号转换成数字信号以后，比特率为8 x8 000 b／s：64 kb／s。将模拟信号用脉冲信号进行采样使其离散化并进行数字编码的过程称为脉冲编码调制，简称PCM，这是将模拟话音信号转换成数字信号的基本方法。
PCM stands for Pulse Code Modulation. PCM technology is a means by which standard audio signals (which are represented by waveforms) are converted to digital audio signals (which are represented by 1 s and 0 s- much like computer data) with little, or no, compression. The method of audio conversion is used on most digital audio formats, including C (2015-11-13, Visual C++, 16KB, 下载2次)
一种HMM可以呈现为最简单的动态贝叶斯网络。隐马尔可夫模型背后的数学是由LEBaum和他的同事开发的。它与早期由RuslanL.Stratonovich提出的最优非线性滤波问题息息相关，他是第一个提出前后过程这个概念的。
在简单的马尔可夫模型（如马尔可夫链），所述状态是直接可见的观察者，因此状态转移概率是唯一的参数。在隐马尔可夫模型中，状态是不直接可见的，但输出依赖于该状态下，是可见的。每个状态通过可能的输出记号有了可能的概率分布。因此，通过一个HMM产生标记序列提供了有关状态的一些序列的信息。注意，“隐藏”指的是，该模型经其传递的状态序列，而不是模型的参数；即使这些参数是精确已知的，我们仍把该模型称为一个“隐藏”的马尔可夫模型。隐马尔可夫模型以它在时间上的模式识别所知，如语音，手写，手势识别，词类的标记，乐谱，局部放电和生物信息学应用。
隐马尔可夫模型可以被认为是一个概括的混合模型中的隐藏变量（或变量），它控制的混合成分被选择为每个观察，通过马尔可夫过程而不是相互独立相关。最近，隐马尔可夫模型已推广到两两马尔可夫模型和三重态马尔可夫模型，允许更复杂的数据结构的考虑和非平稳数据建模。
The HMM is a statistical approach in which the underlying model is a stochastic Markovian
process that is not observable (i.e., hidden) whic h can be observed through other processes that
produce the sequence of observed (emitted) features. In our HMM we let the hidden nodes represent
activities. The observable nodes re present combinations of the features described earlier. The
probabilistic relationships between hidden nodes and observable nodes and the probabilistic transition
between hidden nodes are estimated by the relative fr equency with which these relationships occur in
the sample data. An example HMM for three of the activities is shown in Figure 3. Given an input
sequence of sensor events, our algorithm finds the mo st likely sequence of hidden states, or activities,
which could have generated the observed event sequence. We use the Viterbi algorithm to
identify this sequence of hidden states. (2015-08-27, C/C++, 37KB, 下载17次)
使用m文件产生加噪声的射频信号，通过滤波得到中频信号和基带信号，然后对其取倒谱。经过门特卡罗仿真，采用统计方式，得到各点的概率分布律，然后计算结果的香农熵和互雷尼信息熵。
M files generated using the RF signal plus noise, obtained by filtering the IF signal and baseband signal, and then take its cepstrum. After the door Monte Carlo simulation, using statistical methods to obtain the probability distribution law of each point, and then calculate the result of Shannon entropy and mutual information entropy Rainey. (2013-10-09, matlab, 24KB, 下载13次)
提出了一种支持矢量机的汉语声调识别新方法。论文首先在基频和对数能量的基础上，建立了一个适合于支
持矢量机分类的等维声调特征。然后对支持矢量机的多分类策略和不同核函数对声调识别的影响进行了实验研究。
与BP神经网络相比，支持矢量机具有更高的识别率和更强的推广能力。
This paper presents a novel support vector machine based Chinese tone recognition method．A
new tone recognition feature is first ex血acted using the fundamental frequency(FO)and logarithmic
energy．And how to select the method of SVM multi-class classification and kernel function is also discussed
by experiments．Compared with BP neural network，SVM has higher recognition rates and more strong
generalization． (2012-10-12, matlab, 461KB, 下载16次)
本 文 首先 介绍了语音识别的研究和发展状况，然后循着语音识别系统的处理过程，介绍了语音识别的各个步骤，并对每个步骤可用的几种方法在实验基础上进行了分析对比。研究了语音信号的预处理和特征参数提取，包括括语音信号的数字化、分帧加窗、预加重滤波、端点检测及时域特征向量和变换域特征向量.其中端点检测采用双门限法.通过实验比对特征参数的选取，采用12阶线性预测倒谱系数作为识别参数。详细分析了特定人孤立词识别
This paper first introduces the research and development of speech recognition, and then follow the process of the speech recognition system, describes the various steps of the speech recognition, several methods are available and each step were analyzed and compared on an experimental basis. Study of the speech signal preprocessing and characterized parameter extraction, including voice signals of the digitization, stars frame windowed pre heavier filtering, endpoint detection timely domain feature vectors and transform domain feature vector. Wherein the endpoint detection using double doors limit law. By experiment than the characteristic parameters of the selected 12 order linear prediction cepstral coefficients as recognition parameters. A detailed analysis of a specific isolated word recognition (2012-08-25, C/C++, 2433KB, 下载23次)
通过核 K- 均值聚类的方法对语音帧进行聚类 , 由于聚类的中心能够很好地代表类内的特征, 用中心样本帧取代该类, 减少了核矩阵的维数, 然后再采用稀疏 KPCA方法对核矩阵进行特征提取。
Through the nuclear K-means clustering method for clustering of speech frames, the cluster center can be a good representative of the class characteristics of the sample frame to replace the class with the center, reducing the dimension of the nuclear matrix, and then use Sparse KPCA method for feature extraction of the nuclear matrix. (2011-11-17, matlab, 181KB, 下载71次)
西奥多里蒂斯著，李晶皎译
本书系统阐述了模式识别的原理与方法，并在此基础上介绍了模式识别的应用。全书分为：基础部分和应用部分：基础部分主要包括统计模式识别、模糊模式识别、神经网络模式识别等内容；应用部分有车牌识别和语音识别。
This paper discussed the principles and methods of pattern recognition, and based on this, the application of pattern recognition. Encyclopedia is divided into: basic part and application part: basic parts mainly include statistical pattern recognition, the fuzzy pattern recognition, neural network pattern recognition content Application part have license plate identification and voice recognition. (2011-09-13, matlab, 8360KB, 下载24次)
《模式分类》(原书第2版)已被卡内基-梅隆、哈佛、斯坦福、剑桥等120多所大学采用为教材。本书作为流行和经典的教材和专业参考书，主要面向电子工程、计算机科学、数学和统计学、媒体处理、模式识别、计算机视觉、人工智能和认知科学等领域的研究生和相关领域的科技人员。开发和研究模式识别系统的实践者，无论其应用涉及语音识别、字符识别、图像处理还是信号分析，常会遇到需要从大量令人迷惑的技术中做出选择的难题。这本独一无二的教材及专业参考书，为你准备了充足的资料和信息，供你选择最适合的技术。
"Pattern Classification" (the original book version 2) has been Carnegie- Mellon, Harvard, Stanford and Cambridge, more than 120 universities use for teaching purposes. Book as popular and classic textbooks and professional reference books, mainly for electrical engineering, computer science, mathematics and statistics, media processing, pattern recognition, computer vision, artificial intelligence and cognitive sciences graduate student and related fields IT staff.
(2011-08-29, PDF, 7483KB, 下载19次)
本 文 首先 介绍了语音识别的研究和发展状况，然后循着语音识别系统的
处理过程，介绍了语音识别的各个步骤，并对每个步骤可用的几种方法在实
验基础上进行了分析对比。研究了语音信号的预处理和特征参数提取，包括
语音信号的数字化、分帧加窗、预加重滤波、端点检测及时域特征向量和变
换域特征向量.其中端点检测采用双门限法.通过实验比对特征参数的选取，
采用12阶线性预测倒谱系数作为识别参数。详细分析了特定人孤立词识别算
法，选定动态时间弯折为识别算法，并重点介绍其设计实现。
在 Vi su alC++环境下，设计并实现一个特定人、孤立词语音识别系统，
系统可以识别数字0-9等简单指令。该系统还具备演示、学习功能，可以演
示语音处理的各个步骤，还可以根据需要添加新的指令。
最 后 ， 重点从端点检测算法和动态时间弯折识别算法对系统进行改进。
实验表明，改进后的系统识别率有很大提高，达到95 ，为进一步开发实用
性语音识别系统产品打下了基础。
This article introduced the first speech recognition research and development, and then follow the voice recognition system
Processing, speech recognition, introduced the various steps, each step of the methods available in the real
A post-mortem conducted on the basis of the analysis and comparison. Research on the speech signal pre-processing and feature extraction, including
Digitized voice signals, sub-frame window, pre-emphasis filtering, endpoint detection feature vector in time domain and variable
Eigenvector for the domain. One endpoint detection method using dual-threshold. Through experiments over the selection of characteristic parameters,
The use of 12-order linear prediction cepstral coefficients as recognition parameters. Detailed analysis of the specific operator who isolated word recognition
Law, selected Dynamic Time Warping Algorithm for identifying and focusing on the achievement of its design.
In Vi su alC++ environment, design and realization of a s (2009-05-15, C/C++, 2433KB, 下载356次)
为虚拟管家系统设计一个麦克风阵列接口，该接口用于接收语音信号作为命令，由麦克风接收识别后用来控制虚拟管家，进而控制各种家用电器工作。当用户移动时，该接口可以跟踪定位用户（此应用中只需知道用户方向角，也是一维定位），即可随时响应用户的控制命令
Housekeeper system for the design of a virtual microphone array interface, the interface for receiving voice signal as a command, from the microphone after receiving recognition used to control a virtual butler, thereby control the various kinds of electrical work. When the user moves, the interface positioning to track users (this application only need to know the user direction angle, but also one-dimensional positioning), at any time in response to the user' s control commands (2009-03-06, matlab, 1618KB, 下载23次)
本书的第1版是模式识别领域的奠基性著作。而今，Stork博士又从近年这一领域的最新成果中精选出重要的内容，对模式识别领域的发展进行了新的总结，并指明了对未来30年至关重要的问题。本书简明易读，新增的图表使得许多统计和数学题材非常生动，最终以完美和谐的形式，引导读者深入各种新的主题。” ——Sargur N．Srihari博士，纽约州立大学布法罗分校计算机科学与工程学教授开发和研究模式识别系统的实践者，无论其应用涉及语音识别，字符识别。图像处理还是信号分析，常会遇到需要从大量令人迷惑的技术中做出选择的难题。这本独一无二的教材及专业参考书，为你准备了充足的资料和信息，帮你选择最适合的技术。作为几十年内模式识别领域经典著作的新版，这一版本更新并扩充了原作，重点介绍模式分类及该领域近年来的巨大进展。本书已被卡内基-梅隆、哈佛、斯坦福、剑桥等120多所大学采纳为教材。
The book version 1 is the field of pattern recognition of the foundation-laying works. Today, Stork Dr. recent years from the latest achievements in this field in the selection of important content, the development of the field of pattern recognition to a new conclusion, and to specify the next 30 years on the crucial issue (2004-06-28, WINDOWS, 6896KB, 下载377次)