基于WINDOWS的SVM的开发工具，特别适合初学者，不需要太了解SVM原理...

静态Huffman的小程序，帮助理解Huffman的原理，不可多得。-small procedure to help understand the principle Huffman indeed.

txt2wav.rar文本语音（Text-to-Speech，以下简称TTS），它的作用就是把通过TTS引擎把文本转化为语音输出。代码示范了如何运用Microsoft Speech SDK 建立自己的文本语音转换应用程序。应该事先下载微软的语音SDK里面含微软的语音开发工具原来是sapi5.1现在好像升级了微软的MSDN上有下-txt2wav.rar text pronunciation (Text-to-Speech, hereafter refers to as TTS), its function is transforms through the TTS engine the text as the pronunciation output. How did the code demonstrate has established own using Microsoft Speech SDK text pronunciation transformation application procedure. Should beforehand download Microsoft inside pronunciation SDK to contain Microsoft the pronunciation development kit originally is sapi5.1 now looks like promotes on Microsoft s MSDN to have next

SVM-light与matlab的接口,matlab下就能直接调用哟,很有价值哟-SVM-light and Matlab interface directly with Matlab can call yo, value yo

语音识别 语音识别 语音识别 -Speech Recognition Speech Recognition Speech Recognition Speech Recognition Speech Recognition Speech Recognition

凌阳61做的语音报站，已经通过调试。-do voice stations, has passed testing. Haha

非常好的音频频谱分析工具，并能够可视化显示。共有EQ Mode/spectrum/pick等六种显示模式。

语音识别专辑五- Speech recognition special edition five

CMU大名鼎鼎的SPHINX－3大词汇量连续语音识别系统，应用于Unix和Windows，做语音识别的必备工具。-CMU famous SPHINX-3 large vocabulary continuous speech recognition system, used in Unix and Windows, so the essential voice recognition tools.

基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration.

对数运算实现是32位的运算包含有指数和对数的求法 -LOG