FIR

用NLMS实现对语音的回声的消除,共4个文件,语音原声,语音回声,NLMS的实现,回声路径(Using NLMS realize voice echo on the elimination of a total of four documents, voice, soundtrack, voice echo, NLMS realization echo path)

语音压缩和回声消除，支持LINUX和其他平台(voip echo cancellation)

一个语音分析程序，包含gammatone滤波器组的分解和重组。对学习语音分析的很有帮助(A speech analysis program contains the gammatone filter group decomposition and reorganization. Helpful learning speech analysis)

熵值越大则每个符号包含的平均信息量越大。有研究发现，在有噪声的语音信号中，语音信号的熵和噪声信号的熵存在着较大的差异，对噪声信号来说在整个频带内分布相对平坦，熵值小，语音信号集中在某些特定频段内，熵值大。因此利用这个差异可以区分噪音段和语音段。(The greater the entropy is, the greater the average information of each symbol is. It is found that, in noisy speech signals, the entropy of speech signals and the entropy of noise signals are quite different. For noisy signals, the distribution is relatively flat in the whole frequency band, and the entropy value is small. The speech signal is concentrated in some specific frequency bands, and the entropy value is large. So the difference can be used to distinguish the noise segment and the speech segment.)

　提出了一种新的连续型隐马尔可夫模型(HMM ) 的概率密度函数, 并导出了一系列的参 数寻优迭代公式,(A new Continuous Hidden Markov Model (HMM) of the probability density function, and derived a series of parameters optimization iteration formula,)

在MATLAB中完成对语音的梅尔倒谱系数的提取(Extraction of Mel cepstrum coefficients)

语音的识别的前端技术，语音的基音周期检测(Front-end voice recognition technology, Voice Pitch Detection)

espeak语音生成库，内附有移植使用文档《espeak移植使用》(espeak speech generation library, containing transplanted using the document espeak transplant use )

System Time Modifier ModifySysTimeItem

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.)