GMM-apply-for-text-to-speech

简单语音识别源码是一个调用讯飞语音识别SDK的例子源码是一个最纯净的Demo比较容易看懂。实现的是点击按钮开始语音监听，手机需要联网，2/3G的均可，识别后会以Toast的方式提示出来，识别率还是比较高的。之前自己是用别人的Demo总是不成功，是因为，讯飞的SDK想使用是需要APPID的，可能过太长时间久会注销，还有，未通过审核的APPID每天只能试用500次，如果太多人试用，就是达到上限导致无法使用。(A simple speech recognition source code is a call Ifly speech recognition SDK example source code is a demo of the purest easier to understand. The realization of the click button to start the voice listening, mobile phone need to networking, 2/3G can, after the recognition will be prompted by Toast way out, the recognition rate is still relatively high. Before he is with someone else s demo is not always successful, is because the Xunfei SDK to use is appid, may be too long for a long time will be canceled, and not through the audit appid every day can only be tried out 500 times, if too many people tried is reaching the limit to use.)

采用加权网络中节点强度和权重都是幂率分布的模型，计算两个矩阵之间的欧氏距离，实现了对10个数字音的识别。( Using weighted model nodes in the network strength and weight are power law distribution, Calculation of the Euclidean distance between the two matrices, To achieve the recognition of 10 digital sound.)

matlab编写的muCVSD语音编码解码器，参数可调，十分方便(matlab prepared muCVSD speech codec parameter adjustable, very convenient)

LMS算法多麦克风语音降噪，语音降噪处理，基于matlab(LMS algorithm for multi-microphone speech noise reduction, voice, noise reduction, based on matlab)

验证码小识别源码程序，结合易语言位图支持库，调用易语言模块实现验证码识别。(Little recognition source code program , combined with easy language bitmap support library , call easy language module verification code recognition .)

melp编解码 matlab 程序 (melp codec matlab program)

语音信号分帧后，计算每帧信号的短时平均能量(After the speech signal is framed, the short-term average energy of each frame signal is calculated)

matlab代码，语音的压缩和编码，主要利用了心理声学模型，得到低比特编码 和高质量语音(matlab code, voice compression and coding, psychoacoustic model used by low-bit encoding and high-quality voice)

线性预测倒谱系数（Linear Prediction Cepstrum Coefficient,LPCC）是线性预测系数（Linear Prediction Coefficient,LPC）在倒谱域中的表示。该特征是基于语音信号为自回归信号的值设，利用线性预测分析获得倒谱系数。(Linear Prediction Cepstrum Coefficient)

gmm模型下的语音情感识别系统，GMM只是一个数学模型，只是对数据形态的拟和，但是和你所看到的数据分布存在出入也是正常的，因为用EM估计GMM的那些参数时，一般假设我们所得到的数据是不完备的（也就是说假设我们看到的数据分布不是真正的分布，它在运算时把那部分丢失或者叫隐藏的数据“补”上了）(gmm model speech emotion recognition system, GMM is a mathematical model, but fitting the data form, but you can see there is access to the data distribution is normal, because those with the EM estimated GMM parameters, the general assumption we get the data is incomplete (that is, assuming we see the distribution of the data distribution is not real, it is part of the operation at the time that is lost or hidden data is called " fill" on the))