Description: 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. Platform: |
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Author:weibaby168 |
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Description: 语音端点检测是语音识别中至关重要的技术。无论军用还是民用，语音端点检测都有着广泛的应用。在低信噪比的环境中进行精确的端点检测比较困难，尤其是在无声段或者发音前后-voice activity detection is critical speech recognition technologies. Whether military or civilian, voice endpoint detection have broad application. Low signal-to-noise ratio in the environment for accurate endpoint detection more difficult, especially in or pronunciation of the silent before and after Platform: |
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Author:李一 |
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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 Platform: |
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Author:意乱 |
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Description: 语音信号的端点检测matlab程序，利用短时平均能量和短时平均过零率判断语音端点的起始。还有语音信号信噪比的计算程序。-Endpoint detection of speech signal matlab procedures, take advantage of short-time energy and short-time average zero-crossing rate of the average voice activity to determine the start. There are voice signal SNR calculation procedures. Platform: |
Size: 1024 |
Author:高金枝 |
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Description: 利用短时平均能量和短时平均过零率，对语音信号进行端点检测-Average energy use of short-term and short-time average zero-crossing rate, speech endpoint detection signal Platform: |
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Author:陈彪 |
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Description: 语音检测的目的是在一串连续的记录信号中将重要的信息分离出来。在电信应用领域，语音检测是必需的。对于自动语音识别，端点检测在分离重要语音信息时是必需的，这样可以产生语音模式或语音模板。-Voice detection is aimed at a string of consecutive records of information important signal will be separated. At the field of telecommunications applications, voice detection is essential. For automatic speech recognition, endpoint detection important voice in the separation when the information is necessary, so that could have a voice pattern or voice template. Platform: |
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Author:candy |
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Description: 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理。-Endpoint detection is the use of digital processing techniques to identify the speech signals in a variety of paragraphs (such as phoneme, syllable, morpheme, word, etc.) the starting point and the end position. Speech endpoint detection is a paragraph beginning and end speech analysis, speech synthesis and speech recognition of a necessary link. Traditional endpoint detection method is to obtain from the wav file voice sampling, its sub-frame and calculate the short-term energy and zero-crossing rate parameters, and then proceed to endpoint detection. This work is called off-line approach can not achieve real-time speech signal processing, analysis of the speech signal has a certain limitations. In this paper, through the development of ActiveX controls, in the MATLAB environment to embedded figure window to use GUI program, the realization of speech signal processing real-time endpoint detection. Platform: |
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Author:cike |
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Description: 这个里面的程序是关于语音信号的端点检测的matlab资料-The inside of the program is on the endpoint detection of speech signal data matlab Platform: |
Size: 2048 |
Author:piaoxue |
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Description: 语音端点检测，有助于除去语音信号中的噪音部分，留下有用的携带信息的部分，有利于提取其中有用的语音特征参数，从而提高识别率。-Endpoint detection, helps remove the noise part of the speech signal, leaving useful information-bearing part, is conducive to extract the speech feature useful to improve the recognition rate. Platform: |
Size: 2048 |
Author:解德鹏 |
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Description: 语音增强是影响语音识别系统性能的重要成分。为了比较语音增强算法的性能，采用Matlab软件进行了数值仿真，对不同噪声环境下的语音用3种不同的方法进行降噪，采用信噪比、端点检测等方法来降噪效果，并对几种增强算法的性能进行了比较分析。结果表明，在变噪声环境下短时谱MMSE法最佳，谱减法和维纳滤波法各有优点。-Speech enhancement of voice recognition is an important component of system performance. In order to compare the performance of speech enhancement algorithm using the Matlab software, a numerical simulation, speech under different noise environments with 3 different methods of noise reduction, the use of signal to noise ratio, endpoint detection method to the noise reduction effect, and a few kinds of enhanced performance of the algorithm were compared. The results show that changing the noise environment in the MMSE method was the best short-term spectrum, spectral subtraction and Wiener filtering methods have their advantages. Platform: |
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Author:static |
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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. Platform: |
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Author:liuhongfu |
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Description: 语音信号双门限法端点检测的matlab程序，用于语音信号的处理-Double threshold method of voice signal endpoint detection matlab program for speech signal processing Platform: |
Size: 1024 |
Author:victor |
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Description: 使用matlab实现的基于短时能量和过零率的语音信号端点检测-The endpoint detection of speech signal based on short-time energy and zero crossing ratio using matlab Platform: |
Size: 60416 |
Author:苏永刚 |
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Search - Endpoint detection of speech signal matlab