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 Platform: |
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Author:小英 |
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Description: 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 Platform: |
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Author:沈雨祥 |
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Description: 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 case (including operating procedures), involving haze denoising, sheet automatic marking, lung image segmentation, wavelet digital watermarking, image retrieval, face recognition, license plate location and two-dimensional code recognition, image compression, Hoffman handwritten digit recognition, character recognition, text English anterior segment tissue extraction, panoramic image mosaic, image fusion, light control, analog audio signal of speech recognition pavement crack detection and identification, video tracking, motion estimation of Simulink image processing technology based on a number of important) Platform: |
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Author:糖糖的小糖
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Description: 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 signal is divided into finite number of frames. Every frame of the speech
signal is assumed to be generated from any one of the n states. Each state is modeled as the multivariate Gaussian density function with the specified mean vector
and the covariance matrix. Let the speech segment for the particular isolated word
is represented as vector S. The vector S is divided into finite number of frames
(say M). The i th frame is represented as Si . Every frame is generated by any of the n
states with the specified probability computed using the corresponding multivariate
Gaussian density model. Platform: |
Size: 787456 |
Author:Khan17
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Description: 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) Platform: |
Size: 3479552 |
Author:Joker298
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Description: 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 calculated and displayed. According to the principle of spectrogram display language, programming implementation period of the speech spectrum diagram calculation and display, and as often as possible language phonetic characteristics of spectra contain information provided by the MATLAB cepstrum calculation function, according to the voice of the complex cepstrum and cepstrum) Platform: |
Size: 282624 |
Author:这些成分
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Description: 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 cepstrum coefficient of unvoiced and voiced sounds
2. Use Matlab to plot the time domain waveform of the speech segment, short-term energy, short-term average amplitude, short-term zero-crossing rate, and short-term overshoot ratio.
3. Select an unvoiced, unvoiced, and voiced sound and use Matlab to plot its logarithmic amplitude spectrum) Platform: |
Size: 146432 |
Author:jacek |
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Search - speech segment matlab