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一个盲信号分离的卷积方法，适合分离实际卷积混合的模型，希望对初学者有帮助。(Convolution of a blind signal separation method, suitable for separation of the real convolution mixture model, want to help beginners.)

这是科大讯飞的IOS开发文档，可合成语音，可语音识别(MSC Develop Manual for iOS)

最权威和最全面的语音识别的特征提取的 IEEE的期刊论文1980(The most authoritative and comprehensive speech recognition feature extraction of the IEEE Journal Papers 1980)

用C#开发的一个语音朗读程序，可以朗读文章，能运行(C# developer with a voice reading program that can read the essay, can run)

基于语音信号工具箱的隐马尔科夫HMM模型的说话人识别，请联系lishicheng64@126.com(Speech signal based on HMM toolbox Hidden Markov Model speaker recognition, please contact lishicheng64@126.com)

C#版语音识别系统，精准度超强，到得收藏(C# version of the speech recognition system, super accuracy to Favorites)

语音信号的短时分析，主要包括：分帧、短时能量、短时平均幅度、短时过零率、短时自相关函数、短时幅度差、倒谱、复倒谱、lpc系数、lpc谱估计等 绝对保证质量，是保研后导师布置的一些基础程序(Short-time speech signal analysis, mainly including: sub-frame, short-time energy, short-term average, short-time zero-crossing rate, short-time auto-correlation function, short-term rate of poor cepstrum, complex cepstrum, lpc coefficients, lpc spectral estimation, such as an absolute guarantee that the quality of instructors is the security arrangement after the inquest some of the basis of procedures)

模拟实验-C#版基于二分查找的稳定“插入排序”算法(Simulation experiment-stable insert sort algorithm based on dichotomous search in C # version)

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.)

科大讯飞语音识别最新Demo,国内优秀的语音识别平台(new demo)