可以讲mulaw语音数据转换成线性pcm数据

在linux平台下,纯c写的盲信号分离的代码.它采用基于卷积混合的盲信号分离算法,不但可以分离人工合成的混合信号,而且对于真实环境中的卷积混合的语音信号也能够分离.在本程序中,包含了两个测试文件,makefile后便可以直接使用. 另外值得一提的是,压缩包里包含有一些语音处理方面的常用函数.例如fft变换,读取写入wav文件,以及一些常用的一维向量和二维矩阵变换的函数.这些可以直接应用在其他应用程序里去.-in linux platform, net write c Blind Signal Separation code. it is based on convolution of mixed Blind Signal Separation algorithm, not only can be separated from the artificial synthesis of mixed-signal, but for the real environment convolution of mixed voice signals can be separated. in this procedure, the tests included two documents, makefile can be used directly after. Also worth mentioning is that Compression bag containing some of voice processing functions commonly used. fft transform, for example, to read write wav file, and some of the commonly used one-dimensional and two-dimensional vector matrix transformation functions. these can be directly applied to other applications going.

数字音频格式有很多种，其质量与采样频率和采样精度两个参数有关。频率的表示单位为赫兹〔Hz〕，它表示每秒采样次数。采样频率越高，音质就越好。采样精度为每次采样所存储的数据数量，它决定每个数字信号所能够表示的离散振幅的数量。存储每个样本的数据越多，音质就越好。但是高品质的声音需要占用大量的内存和磁盘空间。考虑到网络带宽，在Internet连接上传输就需要花费很长的时间。对于Applet来说，保证声音文件的最小化是极为重要的。-digital audio format there are many, the quality and frequency of sampling and sampling accuracy of the two parameters. The frequency of Hertz unit of [Hz], it said the number of samples per second. The higher sampling frequency, the sound quality better. For each sampling precision sampling by the amount of data storage, it was decided that each digital signal can be expressed as the number of discrete amplitude. Each sample storage of more data, better sound quality. But high-quality voice would take a lot of memory and disk space. Consideration of the network bandwidth, the transmission on the Internet connection on the need to spend a very long time. Applet for instance, to ensure that voices of the smallest document is very important.

ETSI发布的用于研究分布式语音识别的前端降噪代码-ETSI issued for the study of Distributed Speech Recognition front Noise Code

MPEG4音频编码器的源码，主要供从事音频/语音编/解码工作的朋友参考

隐马尔科夫模型实现语音识别，该模型具有较好的识别效果，主要针对的是本科生的课程项目，有一定的学习价值。

语音信号的频域处理,语音虽然是一个时变、非平稳的随机过程。但在短时间内可近似看作是平稳的。因此如果能从带噪语音的短时谱中估计出“纯净”语音的短时谱，即可达到语音增强的目的。由于噪声也是随机过程，因此这种估计只能建立在统计模型基础上。利用人耳感知对语音频谱分量的相位不敏感的特性，这类语音增强算法主要针对短时谱的幅度估计。 -voice signals in the frequency domain processing, voice is a time-varying, nonstationary random process. But in a short period of time can be approximated as smooth. So if Noisy Speech from the short-term spectrum estimate "pure" voice of the short-term spectrum, and reached speech enhancement purposes. As the noise is random process, which can only be estimated based on statistical models based on. Use ear perception of voice spectrum component of the phase sensitive to the characteristics of such speech enhancement algorithms targeted at the rate of short-term spectral estimation.

语音识别与合成入门4，word或压缩包中内有matlab源码-speech recognition and synthesis four entry, word or compressed packages within Matlab FOSS

自编的几个关于数字信号基本运算的程序，由此可以大大扩展信号运算的自由性与简洁性。-wrote several digital signal on the basic operations procedures, It can be greatly expanded signal operation and the freedom of simplicity.

检测语音信号的共振峰 ％ gender = gender_detector(X,Fs) ％ ％ This function will use a pitch detection algorithm to decide if the speaker is MALE(0) or FEMALE (1). ％ It is designed to work with short speech samples (up to or greater than 50 ms). The function returns a ％ 0 if X contains male speech and a 1 if it contains female speech. -the resonance peak gender_detector% gender = (X, Fs)%% This function will use a detection a pitch lgorithm to decide if the speaker is abbreviation (0) or F EMALE (1). % It is designed to work with short spe ech samples (up to or greater than 50 ms). The fun ction returns a 0% if X contains a male speech and if it contains a female speech.

用于语音识别的盲信号，应用开发环境maltab编写的代码，