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机器人语言控制系统
- vc++6.0 开发的机器人语言控制系统,能够用语音同过串口通讯命令机器人执行诸如:上升、下降、大臂运行、大臂归零等命令-vc 6.0 development language robot control system can be used with voice communications over serial order robot such as : up, down, the running boom, boom, such as zero order
exp_001
- 自己用VC编写的一个读取wave文件，并计算短时能量、短时过零率以及自相关函数的程序。所有的计算结果都会显示在程序运行后生成的文本文档中。注意，运行程序时需要修改wave文件路径，在程序中体现为wavefilename字符串指针所指向的内容。-own VC prepared a document reader wave and short-term energy calculation, Short-term rates and zero autocorrelation function pro
tdpsola
- 此算法是针对语音合成，采用时域的基音同步叠加算法，对波形进行韵律特征提取，修改，以及合成（包括短时能量分析，短时过零率分析等等算法）！算法是用matlab编写的-Speech synthesis, using time-domain synchronous Pitch stack algorithm, rhythm right waveform feature extraction, modification, and synthesis (including short-term energy
voiceboxnew
- 我新下载到的一个语音工具包，不知道大家看没看过，所以传上去跟大家共享一下-I downloaded the new voice of a tool kit, I do not know if you do not read, follow-up share what
speakerrecognition
- 语音识别中的两种特征提取方法lpcc和mfcc，还有一个是文本无关的识别算法dtw，另外还有一个是预处理消噪部分的。共享一下，这些都是我调试过的，好用。-Speech Recognition two feature extraction methods and mfcc lpcc. There is a text-independent recognition algorithm dtw, in addition to a pretreatment is part of the noise so
speechacquired
- 这个是实时采集语音信号，以及小波消噪的运行程序，我用过的，还算可以，但是小波消噪的那个程序有点问题，大家如果运行后，发现问题出在什么地方，谢谢告诉我。-This is a real-time voice signal acquisition and wavelet denoising operating procedures, I used that figure, Wavelet denoising but that the process is flawed, and if we run,
endpointvad
- 自已编写的语音信号端点检测程序，采用短时能量与短时过零率的方法。-authorship of the speech signal endpoint detection procedures, using short-term over short-term energy and the rate of zero.
zishiyinglms
- 自适应滤波器的LMS算法希望能够对大家有所帮助，这各算法是实现过了的，可是运行，图像还比较令人满意，要是大家下载了，请留下评价-LMS adaptive filter algorithm hope to be helpful to everyone, the algorithm is realized in a, However operation, image is relatively satisfactory, if you download, please leave Evaluatio
DespPitchSpeakerRecog
- 关于说话人识别方面的五个子程序，包括倒谱基音周期混合特征系数的话者识别，能频积端点检测、语音基音周期检测等C++源代码，本人整理编译过，比较紧凑高效；-Speaker Recognition of the five subroutines, including cepstrum Pitch mixed coefficient of the recognition, the frequency can plot endpoint detection, Pitch detection C sourc
endpoint.rar
- 端点检测（短时能量，短时平均幅度，短时过零率）,short-term spectrum，spectrogram，End point detection
speech
- 语音参数短时能量，短时过零率，短时平均幅度，语音端点检测，fft变换与反变换-Voice parameters of short-time energy, short-time zero-crossing rate, short-term average rate, voice activity detection, fft transform and inverse transform
speech
- 语音信号时域特性分析，包括时域谱，短时过零率分析，短时幅值，短时能量，自相关函数-Analysis of time-domain characteristics of speech signals
matlab
- MATLAB下实现语音断点的完全仿真，加入了语音能量和过零率的比值一一对应。-MATLAB realization of the complete simulation breakpoint voice, joined the Voice of energy and zero-crossing rate of one-to-one ratio.
fenzhenchuli
- 语音特征提取，如过零率，能量比，短时能量。须导入MAV音频。-Voice feature extraction, such as zero-crossing rate, energy ratio, short-term energy. MAV audio to be imported.
frame
- 读取语音文件 进行分帧加窗 及计算语音文件短时能力和过零率。可用于对音乐哼唱检索系统的开发及研究学习。-Voice files to read sub-frame and calculation of windowed audio files and short-term zero-crossing rate. Music can be used to Query by Humming system development and research study.
F2_6764
- 端点检测是指用数字处理技术来找出语音信号中的各种段落（如音素、音节、词素、词等）的始点和终点的位置。语音段起止端点检测是语音分析、语音合成和语音识别中的一个必要环节。传统的端点检测方法是从wav文件中获取语音采样，将其分帧并计算短时能量和过零率参数，然后进行端点检测。这种工作方式被称为离线处理方法 ，无法实现语音信号的实时处理，对于语音信号分析具有一定的局限性。本文通过开发ActiveX控件，在MATLAB环境下将其嵌入到figure窗口中，以GUI程序的方式使用，实现语音信号端点检测的实时处
yuyin
- 时域波形、短时能量、短时平均幅度、短时过零率、短时过电平率-Time-domain waveform, short-term energy, short-term average rate, short-term zero crossing rate, short-term rates over Level
Speechrecognitiontechnology
- 比较详尽的介绍了语音识别系统的实现过程，以及相关技术。 端点检测：基于短时能量和短时平均过零率的端点检测和基于倒谱特征的端点检测 特征参数提取：LPCC和MFCC 参数模板存储：HMM和N_Gram 识别阶段：DWT 各阶段的相关技术都给了详细的介绍，绝对是好东西！-More detailed introduction to the speech recognition system implementation process and related technologie
过零率计算源代码
- 语音端点的检测，不能只以能量的大小进行检测。人声和周边噪音，都可能拥有足够的能量，因此单独能量无法准确检测端点。而过零率在这一点上，则可以起到很大的效果。因此，端点检测时，过零率是不可以缺少的。(Adding zero crossing rate, can accurate detect. Human speech has more zero crossing rate.)
short_zero_crossing_rate
- 语音信号的短时过零率求取，此过程为语音信号的一个重要特征提取过程，可用于端点检测等过程。(This process is an important feature extraction process for speech signals and can be used for endpoint detection and other processes.)