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Description: 语音端点检测算法，在matlab里面实现语音端点的准确检测。为读者开发噪声环境下的精确VAD提供思路。-voice endpoint detection algorithm in Matlab voice inside the precise endpoint detection. Readers development under noisy environments to provide accurate VAD ideas.
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Size: 1296 |
Author: 王雷 |
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Description: 语音端点检测算法，在matlab里面实现语音端点的准确检测。为读者开发噪声环境下的精确VAD提供思路。-voice endpoint detection algorithm in Matlab voice inside the precise endpoint detection. Readers development under noisy environments to provide accurate VAD ideas.
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Size: 1024 |
Author: 王雷 |
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Description: 本课题为给语音识别系统提供语音信号端点检测的功能，对语音信号端点检测进行了探讨和研究,主要是侧重语音区间的端点检测...(附软件源码)-Voice Active Detection (VAD) is discussed in this project. Detection between speech section and speechless section and emphasized.(code available).
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Size: 272384 |
Author: 黄如意 |
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Description: 这里是几篇关于语音增强中有声无声估计的VAD算法的文献，希望和大家一起讨论，做出与之相关的matlab源代码。-Here are a few on the speech enhancement in a silent voice has estimated VAD algorithm literature, hope and everyone together to discuss and make related matlab source code.
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Size: 1731584 |
Author: rube |
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Description: VAD算法的源程序，可用于静音检测方面算法的参考-VAD algorithm source code can be used to mute the reference testing algorithm
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Size: 41984 |
Author: 辛沂 |
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Description: matlab开发环境下的谱减法算法，主要用在了作者的语音增强算法当中-development environment under matlab spectral subtraction algorithm, mainly used in the author
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Size: 1024 |
Author: wanghang |
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Description: 语音信号处理，mel端点检测在几种降噪方法之后的检测效果-Speech Signal Processing, mel Endpoint Detection of several noise reduction methods in the detection of the effect of
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Size: 5120 |
Author: 意乱 |
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Description: 自己写的关于语音识别技术中预处理过程中端点检测技术源码，用的matlab语言-Wrote it myself on voice recognition technology in the pretreatment process endpoint detection technology source, using the matlab language
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Size: 1024 |
Author: 李正 |
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Description: 语音端点检测算法，在matlab里面实现语音端点的准确检测。为读者开发噪声环境下的精确VAD提供思路.-voice endpoint detection algorithm in Matlab voice inside the precise endpoint detection. Readers development under noisy environments to provide accurate VAD ideas.
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Size: 1024 |
Author: 杨锐雄 |
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Description: 在语音识别系统中，端点检测的目的是要区分语音段和非语音段 ,它在自动语音识别中起着关键作用-In speech recognition systems, the purpose of endpoint detection is to distinguish between voice and non-voice segment, which in automatic speech recognition plays a key role
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Size: 1024 |
Author: 小英 |
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Description: 几篇带噪声语音信号端点检测算法的论文，希望对大家有用-Speech signal with noise several endpoint detection algorithm for papers, in the hope that useful
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Size: 1235968 |
Author: 毋桂萍 |
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Description: 用matlab将hanning窗、hamming窗、Blackman窗画在同一个图中。语音分帧，加窗，短时能量，短时过零率，端点检测-Using matlab to hanning window、hamming window and Blackman window draw in the same graph.Voice sub-frame, add windows, short-term energy, short-term zero-crossing rate, endpoint detection
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Size: 2048 |
Author: haoyy |
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Description: dtw文件是运用DTW算法实现安静环境下语音识别的。其中vad.m是端点检测程序；lpc.m是计算LPC参数的程序；lpc21lpcc.m是计算LPCC参数的程序；mfcc.m是计算MFCC参数的程序；dtw.m是实现经典DTW算法的程序；dtw2.m是实现高效DTW算法的程序，testdtw.m是最终测试程序，其中可以通过改变其中的特征参数名选择不同的特征参数。-dtw file DTW algorithm is to use speech recognition in quiet environments. Which is the endpoint detection process vad.m lpc.m is to calculate the LPC parameters of the program lpc21lpcc.m procedure is to calculate the LPCC parameters mfcc.m procedure is to calculate the MFCC parameters dtw.m the classic DTW algorithm to achieve the program dtw2.m DTW algorithm is to achieve efficient procedures, testdtw.m is the final test program, which can change the parameters in which different parameters were selected.
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Size: 8192 |
Author: 于军 |
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Description: hmm文件时运用HMM算法实现噪声环境下语音识别的。其中vad.m是端点检测程序；mfcc.m是计算MFCC参数的程序；pdf.m函数是计算给定观察向量对该高斯概率密度函数的输出概率；mixture.m是计算观察向量对于某个HMM状态的输出概率，也就是观察向量对该状态的若干高斯混合元的输出概率的线性组合；getparam.m函数是计算前向概率、后向概率、标定系数等参数；viterbi.m是实现Viterbi算法；baum.m是实现Baum-Welch算法；inithmm.m是初始化参数；train.m是训练程序；main.m是训练程序的脚本文件；recog.m是识别程序。-hmm HMM algorithm file using speech recognition in noisy environments. Which is the endpoint detection process vad.m mfcc.m procedure is to calculate the MFCC parameters pdf.m function is calculated for a given observation vector of the Gaussian probability density function of output probability mixture.m is to calculate the observation vector for a HMM state output probability of observation vector is the number of Gaussian mixture per state output probability of the linear combination getparam.m before the calculation of the probability function, backward probability, calibration coefficients and other parameters viterbi.m is Viterbi algorithm implementation baum.m Baum-Welch algorithm to achieve inithmm.m is the initialization parameters train.m is the training program main.m training program is a script file recog.m is to identify procedures.
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Author: 于军 |
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Description: 为提高语音端点检测(VAD)在较低信噪比(10 dB)下的准确率,提出一种基于短时分形维数的改进算法。结合语音信号的特点,对2种常用的语音信号分形维数计算方法进行了比较和选择,同时采用动态跟随门限值实现语音端点的自适应检测。试验结果表明:对于信噪比6~10 dB的带噪语音,此方法可以实现整段语音的检测,而且具有一定的噪声鲁棒性,系统运行期间能够自适应调整门限值以适应环境噪声的变化,提高了VAD算法的准确率。这个是源码matlab。-In order to improve voice activity detection (VAD) in low SNR (10 dB) accuracy under proposed based on short-time fractal dimension of the improved algorithm. Combined with the characteristics of the speech signal, to 2 commonly used fractal dimension of speech signals are compared and calculated choice to follow the same dynamic endpoint threshold adaptive detection of voice. The results showed that: 6 ~ 10 dB for the signal to noise ratio of noisy speech, this method can detect the entire speech, but has some noise robustness, the system can be adaptively adjusted during operation to adapt to environmental noise threshold of changes to improve the accuracy of VAD algorithms. This is the source matlab.
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Size: 79872 |
Author: liuhongfu |
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Description: matlab语音端点检测源码,对非连续性语音具有良好的检测性能-vad in process of speech
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Size: 1024 |
Author: 王涛 |
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Description: 于市售 STM32 开发板上实现特定人语音识别处理项目。识别流程是：预滤波、ADC、分帧、端点检测、预加重、加窗、特征提取、特征匹配。端点检测(VAD)采用短时幅度和短时过零率相结合。检测出有效语音后，根据人耳听觉感知特性,计算每帧语音的 Mel 频率倒谱系数(MFCC)。然后采用动态时间弯折(DTW)算法与特征模板相匹配,最终输出识别结果。先用Matlab对上述算法进行仿真，经数次试验求得算法内所需各系数的最优值。而后将算法移植到 STM32 开发板上，移植过程中根据 STM32 上存储空间相对较小、计算能力也相对较弱的实际情况，对算法进行优化。最终完成于 STM32 微处理器上的特定人语音识别系统。-Implement speech recognition processing project in commercially available STM32 development board. Identification is the process: pre-filter, ADC, framing, endpoint detection, pre-emphasis, windowing, feature extraction, feature matching. Endpoint detection (VAD) short-time amplitude and short-term zero rate combined. After detecting an effective voice, according to the characteristics of human auditory perception, calculated for each frame of speech Mel Frequency Cepstral Coefficients (MFCC). Then dynamic time warping (DTW) algorithm and feature template matches the final output recognition result. First with Matlab simulation algorithm described above, after several trials to get the optimal value of each coefficient within the desired algorithm. The algorithm will migrate to STM32 development board, the porting process according to the STM32 relatively small storage space, computing power is relatively weak situation of the optimization algorithm. Finally completed on the STM32 micr
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Size: 325632 |
Author: Chenkly |
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Description: VAD matlab程序 常见于无声帧检测 语音信号处理(VAD matlab program is commonly used in silent frame detection speech signal processing)
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Size: 3072 |
Author: zhangziju |
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