vadsohn

观测实时模拟信号（语音）的频谱 用音频设备采集一段语音，将语音存为.wav格式。对wav文件作分段傅里叶变换分析。语音是分音节的，应把它分段分析，而且实际运用中的数字信号处理的FFT的点数是有限的，一般只能达到千点。用傅里叶反变换IFFT，从频域恢复信号。画出频谱图和语音波形图。 (Observing real-time analog signal (voice) of the spectrum collected with the audio devices section of voice, voice saved as. Wav format. Wav file of the sub-Fourier transform analysis to make. Speech is divided into syllables, it should be sub-analysis, and practical application of digital signal processing of the FFT points is limited, generally only reach 1000 points. Fourier inverse transform IFFT, to restore the signal from the frequency domain. Draw the spectrum map and voice waveform.)

一个通过实际应用的“ 人工鱼群算法”，效果很好的。(Through the practical application of the " artificial fish-swarm algorithm," good effects.)

Speaker Identification using MFCC feature and VQ training, very clear MATLAB code

使用TD-PSOLA（td-psola、psola）算法，做了一个语音合成，实现语音声调的变调，时长的变化等功能。参考praat源码，提取出其合成方法，效果不错。需要提供pitchtier、durationtier、pointprocess等准换信息文本（可由praat产生）供readfile函数读入(Use TD-PSOLA (TD-PSOLA, PSOLA algorithm, made a speech synthesis, speech tone tone sandhi, long-term changes in the function. Reference Praat source code, extract its synthetic method, the effect of the same.)

本系统是基于矢量量化技术的说话人识别系统。可根据语音库以及实时录音识别且具有图形用户界面。压缩包内含有源码、语音信息库音频及演示视频等。(The system is based on vector quantization speaker recognition system. Identifiable and has a graphical user interface based on speech and real-time recording. Within the compressed package contains the source code, voice information and presentation of audio and video.)

matlab语音识别与分辨，可以做到特定语句的识别和特定人的识别。(Matlab speech recognition and resolution)

Edinburgh Speech Tools for speech synthesis

语音信号的语谱图生成函数，function [ ] = spetro(Winsiz, Shift, Base, Mode, Gray)，5个参数分别为帧长、帧移、取值门限（一般设为0）、彩色模式、灰度模式(This is a matlab function for creating speech spectrogram.)

基于matlab的语言情感识别仿真，可以实现用户注册，识别使用者说话时的喜怒哀乐等情感，人数少时可以实现很高的准确率。(Emotion Recognition based on Matlab language simulation, you can implement user registration, the number of emotions such as feelings, identify the user to speak came from a high accuracy can be achieved.)

gmm模型下的语音情感识别系统，GMM只是一个数学模型，只是对数据形态的拟和，但是和你所看到的数据分布存在出入也是正常的，因为用EM估计GMM的那些参数时，一般假设我们所得到的数据是不完备的（也就是说假设我们看到的数据分布不是真正的分布，它在运算时把那部分丢失或者叫隐藏的数据“补”上了）(gmm model speech emotion recognition system, GMM is a mathematical model, but fitting the data form, but you can see there is access to the data distribution is normal, because those with the EM estimated GMM parameters, the general assumption we get the data is incomplete (that is, assuming we see the distribution of the data distribution is not real, it is part of the operation at the time that is lost or hidden data is called " fill" on the))