yuyinxinhaolianghua

三种降噪，回声和变调的语音信号处理，含UI界面(Three kinds of noise reduction, echo and tone of voice signal processing, including UI interface)

端点检测算法采用现阶段比较精确的时频方差检测法，模式识别和模板匹配采用的是改进后的DTW算法（主要是限定了DTW的搜索路径，进一步精确了DTW的平行四边形的形状，进一步的减少匹配中的参数存贮量以及多余的搜索路径）。(Endpoint detection algorithm uses more precise at this stage variance time-frequency detection, pattern recognition and template matching is based on the improved DTW algorithm (DTW is mainly limited to the search path, and further precision of the DTW parallelogram shape, and further reduction of matching the parameters in the storage volume as well as the extra search path).)

提供了segmantal SNR及IS的计算代码，用于语音增强后评价用。(Provided segmantal SNR and IS calculation code for speech enhancement with post-evaluation.)

PESQ-主观语音质量评估。 ITU-T P.862建议书提供的客观MOS值评价方法。PESQ可以广泛的用于现场和模拟网络中端到端测量。背景(环境)噪声和噪声处理,可以通过用PESQ比较干净的、未处理的信号和编码的、经噪声干扰失真的信号评估得到。(PESQ- subjective speech quality assessment. ITU-T P.862 recommendations for objective MOS value uation method book provides. PESQ can be widely used in the field and in the end measurement analog networks. Background (ambient) noise and noise processing, you can use PESQ relatively clean, unprocessed signal uation and signal encoded by the noise distortion obtained.)

语音信号的时域、频域分析,包括短时能量分析、短时平均过零率、自相关函数、短时平均幅度差函数等。(Time-domain speech signal, frequency domain analysis, including short-term energy analysis, the average short-term zero-crossing rate, autocorrelation function, such as short-time average magnitude difference function.)

基于LPC的语音合成，可以实现变调变速功能，附带注释便于学习。(LPC-based speech synthesis, can achieve modulation speed function, annotated easy to learn.)

一个简易的端点检测程序，已经实现，包括基于过零率、短时能量的双门限判决方法。(a simple endpoint detection procedures has been achieved, including on the basis of zero rate Short-term dual energy threshold judgment method.)

频域的模态参数识别方法之一，可以对振动信号进行分析处理，得出结构的固有频率，阻尼比，振型系数，方法很好，程序完整(Frequency-domain modal parameter identification methods that can analyze the vibration signal processing, draw the structure of natural frequencies, damping ratio, mode shape coefficient, very good method, program integrity)

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.)

基于峭度的盲分离开关算法的matlab源代码程序(Blind Source Separation Based on Kurtosis switch algorithm )