VoiceToWord_yysb

采用MFCC方法提取训练集样本或测试集样本语音特征参数的MATLAB程序，仿真时需先将voicebox语音处理工具箱添加到MATLAB软件中(The MFCC method is used to extract the MATLAB program of the training set sample or the test set sample speech feature parameters. The voicebox voice processing toolbox is added to the MATLAB software first.)

语音处理的实用代码，完成耳语音的声韵分割功能(Practical speech processing code, complete the ear speech sound segmentation function)

分段信噪比测试，主要是用于语音增强，语音编码后的测试使用(segment SNR test, primarily for speech enhancement, speech coding after testing)

通常语音信号在增强时会出现混响现象，演讲者为了消除背景混响，不得不频繁地偏转头部的方向，这样会造成脉冲响应的不断改变。我们结合盲解卷法和频谱消去法来提高逆滤波器的滤波效果。我们利用输入语音信号间的相关系数矩阵计算出稳定、精确的室内脉冲响应的逆滤波器，而这些输入信号无需测量室内的脉冲响应就能被观测到。逆滤波能够消除早期的反射，这些反射包含混响中的绝大部分能量。之后，用频谱消去法来抑制逆滤波后的信号的尾部混响。本方法在实际适应性方面的表现通过具体的实验进行了验证，结果表明盲解卷法和频谱消去法的结合相较于单独使用一种方法，能够提供一个更优越的演说环境。(Usually voice signal will be enhanced when the reverberation phenomenon, the speaker in order to eliminate the background reverberation, and had to frequently deflect the direction of the head, this will cause the impulse response of changing. We combine the blind deconvolution and spectral elimination method to improve the filtering effect of the inverse filter. We use the correlation coefficient matrix between the input speech signal to calculate the stable, accurate inverse filter of the indoor impulse response, and these input signals do not need to measure the room impulse response can be observed. Inverse filtering to eliminate early reflections, these reflections contains most of the energy in the reverberation. After the spectrum elimination method to suppress the tail reverberation of the signal after the inverse filtering. Performance in the actual adaptation of the method by specific experimental validation results show that the blind deconvolution and spectrum to eliminate )

实现已知训练序列的矢量量化器（LBG）算法。初始码书从训练序列每隔五个样本选取一组(Achieve a known training sequence of the vector quantizer (LBG) algorithm. The initial codebook from the training sequence every five samples to select a group of)

Pitch Detection MATLAB

lms alghoiritm method adaptive system

LD3320 是一颗基于非特定人语音识别（SI-ASR：Speaker-Independent Automatic Speech Recognition）技术的语音识别/声控芯片。提供了真正的单 芯片语音识别解决方案。 LD3320 芯片上集成了高精度的A/D 和D/A 接口，不再需要外接辅助的 Flash 和RAM，即可以实现语音识别/声控/人机对话功能。并且，识别的关键词 语列表是可以动态编辑的。(Voice Recognition ；Speech Recognition ；Speech recognition technology )

speech specgram code

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.)