A Review of Off-line Handwritten Chinese Character Recognition

FUNDAMENTALS OF SPEECH RECOGNITION(语音识别基本原理)》(英文)

人脸识别（python）

Face Detection and Recognition: Theory and Practice

Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabulary continuous speech recognition (LVCSR) systems are based on HMMs. Whereas the basic principles underlying HMM-based LVCSR are rather straightforward, the approximations and simplifying assumptions involved in a direct implementation of these principles would result in a system which has poor accuracy and unacceptable sensitivity to changes in operating environment. Thus, the practical application of HMMs in modern systems involves considerable sophistication. The aim of this review is first to present the core architecture of a HMM-based LVCSR system and then describe the various refinements which are needed to achieve state-of-the-art performance. These refinements include feature projection, improved covariance modelling, discriminative parameter estimation, adaptation and normalisation, noise compensation and multi-pass system combination. The review concludes with a case study of LVCSR for Broadcast News and Conversation transcription in order to illustrate the techniques described.

这个是稀疏编码应用与人脸识别，有算法的参考文献集matlab代码，供大家学习参考

模式识别第四版答案（pattern recognition fourth edition solution）

用 matlab开发的说话人识别算法。用到了GMM,DTW等分类算法，还用到了MFCC特征抽取算法等

这个说话人识别代码中包含两个例子，都已经实现。读者需按照里面pdf进行仿真。

人脸识别中常用的一个数据库，Extended YaleB，文件中是已经裁好的图片