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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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gaze tracking system in matlab-used to move a wheelchair for physically challenged people
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用于提取一段语音中单独的每个字词，matlab下编写，经检测很好用。注意不是检测一段语音中的一个字词，而是所有的。-to detect every word in a speech segment. made in matlab. mind you , it s meant to detect every word, not only the first word
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利用MATLAB对语音进行端点检测，检测起始端和终点段-Using MATLAB speech endpoint detection, detecting the start and end segment ends
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可以直接用于MATLAB中的.txt语音片段，浊音片段-Can be directly used for.Txt speech segments MATLAB, voiced segment
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详细讲解了25个MATLAB图像与视频处理实用案例（含可运行程序），涉及雾霾去噪、答题卡自动阅卷、肺部图像分割、小波数字水印、图像检索、人脸二维码识别、车牌定位及识别、霍夫曼图像压缩、手写数字识别、英文字符文本识别、眼前节组织提取、全景图像拼接、小波图像融合、基于语音识别的音频信号模拟灯控、路面裂缝检测识别、视频运动估计追踪、Simulink图像处理等多项重要技术(Explain in detail the 25 MATLAB image and video processing utility
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The speech signal for the particular isolated word can be viewed as the one generated using the sequential generating probabilistic model known as hidden Markov
model (HMM). Consider there are n states in the HMM. The particular isolated
speech sig
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实现了维纳滤波对语音信号的去噪，输入一段音频文件，取单声道，加噪声后进行滤波(Wiener filtering The Wiener filter is used to denoise the speech signal, input a segment of audio file, take the single channel, and filter the noise after adding the noise)
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根据短时傅里叶变换原理，计算并显示该语音段的短时幅度谱和功率谱；根据语谱图显示原理，编程实现该语音段语谱图的计算和显示，并尽量多地分析出语谱图包含的语音特征信息,用MATLAB提供的倒谱计算函数，显示该语音段的复倒谱和倒谱(According to the principle of short-term Fourier transform, the short range spectrum and power spectrum of the speech segment are calculat
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语音信号的时域、频域与倒谱域分析。
1.分析一帧清音和浊音的自相关函数和倒谱系数
2.用Matlab画出该段语音的时域波形、短时能量、短时平均幅度、短时过零率、短时过电平率
3.选择一帧无声、清音和浊音的语音，用Matlab画出它们的对数幅度谱(Time domain, frequency domain and cepstrum domain analysis of speech signals.
1. Analyze the autocorrelation function and c
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