Description: 语音信号的频域处理,语音虽然是一个时变、非平稳的随机过程。但在短时间内可近似看作是平稳的。因此如果能从带噪语音的短时谱中估计出“纯净”语音的短时谱，即可达到语音增强的目的。由于噪声也是随机过程，因此这种估计只能建立在统计模型基础上。利用人耳感知对语音频谱分量的相位不敏感的特性，这类语音增强算法主要针对短时谱的幅度估计。
-voice signals in the frequency domain processing, voice is a time-varying, nonstationary random process. But in a short period of time can be approximated as smooth. So if Noisy Speech from the short-term spectrum estimate "pure" voice of the short-term spectrum, and reached speech enhancement purposes. As the noise is random process, which can only be estimated based on statistical models based on. Use ear perception of voice spectrum component of the phase sensitive to the characteristics of such speech enhancement algorithms targeted at the rate of short-term spectral estimation. Platform: |
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Author:罗飞 |
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Description: 现今市面上流行的一些英语学习软件，在广告词上经常说自己使用了国际顶尖的全程语音TTS技术，能进行整段英文的流利朗
读，并能自由调节朗读的速度与频率等。那么，这个神奇的TTS究竟是什么东西呢？
其实，TTS是微软出品的一套文字朗读引擎（Text-To-Speech Engine)，这些英语软件就是调用它来进行英文朗读的。我们在英语
学习软件的编程开发中也可使用TTS技术，下面笔者将利用Visual Basic 5.0来揭开TTS神秘的面纱。
-current fashion for the English learning software, in the words often said that the use of the international voice of the entire process leading TTS technology, the entire paragraph reads English fluently, and can freely adjust the reading speed and frequency. Well, the magic TTS what exactly is? In fact, Microsoft TTS is the product of a set of text-engine (Text-To-Speech Engine), which is software called English for the English it read aloud. We in the English learning software programming also can use TTS technology, following the author will use Visual Basic 5.0 to open TTS mysterious veil. Platform: |
Size: 69632 |
Author:小炒撒 |
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Description: S变换的matlab源码，并应用几个信号作为例子来说明怎么使用s变换以及s变换可以用来做些什么事情。s变换是时频分析领域中一个较新的内容，现在在信号处理，地震勘探，语音识别等领域都开始了对它的应用研究，是目前的一个热点。-S transform Matlab source, Applied Signal and several examples to illustrate how the use of Transform's's transformation can be used to do anything. Transform's time-frequency analysis is the area of a newer, now in signal processing, seismic exploration, Speech Recognition and other areas has started its applied research, is a hot spot. Platform: |
Size: 339968 |
Author:王清振 |
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Description: 这是一个频减法语音增强算法的matlab代码，在matlab中运行成功的-This is a frequency subtraction speech enhancement algorithms Matlab code in Matlab run successful Platform: |
Size: 1024 |
Author:怀坏 |
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Description: 低频语音识别,可精确识别动物语音,仅此一家-Low-frequency speech recognition, can accurately identify the animal voice, only a Platform: |
Size: 41984 |
Author:艾炜 |
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Description: matlab 源码,基于小波变换的语音信息隐藏的实现,对原始语音信息和水印信息都经过三层小波分解处理后,将水印信息的低频信号嵌入原始语音信号的部分高频信号部分实现隐藏.源代码不仅给出隐藏过程,并且给出的在随机噪声,重采样,信息压缩情况下的抗攻击特性.源代码清晰有注释-matlab source code, based on wavelet transform voice messages hidden realize, the original voice information and watermark information after a three-treatment, after wavelet decomposition, the watermark information embedded in the low-frequency signals of the original speech signal realize some hidden part of high-frequency signals. source code is given not only to hide the process, and given in random noise, resampling, compression of information in case of anti-attack features. source code has a clear Notes Platform: |
Size: 1024 |
Author:桑圣洁 |
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Description: Generalized Mel frequency cepstral coefficients for large-vocabulary Speaker-Independent Continuous-Speech Recognition 关于MFCC算法的很好的英语文章-Generalized Mel frequency cepstral coefficients for large-vocabulary Speaker-Independent Continuous-Speech Recognition on the MFCC algorithm is a very good article in English Platform: |
Size: 165888 |
Author:xiang |
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Description: 录制一段个人自己的语音信号，并对录制的信号进行采样；画出采样后语音信号的时域波形和频谱图；给定滤波器的性能指标，采用窗函数法和双线性变换设计滤波器，并画出滤波器的频率响应；然后用自己设计的滤波器对采集的信号进行滤波，画出滤波后信号的时域波形和频谱，并对滤波前后的信号进行对比，分析信号的变化；回放语音信号；最后，设计一个信号处理系统界面。-Record a person s own voice signal, and recording the signal sampling draw sample after the speech signal time-domain waveform and frequency spectrum given filter performance indicators, using a window function method and the bilinear transform filter design and draw the frequency response filter then use the filter of their own design for the signal acquisition filtering, after filtering the signal to draw the time-domain waveform and spectrum, and filtering of signals before and after contrast, analysis of signal changes playback of voice signal Finally, the design of a signal processing system interface. Platform: |
Size: 2048 |
Author:yim |
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Description: praat中文指导手册，指导基本语音分析方法和提取基频等等基本操作-praat English instruction manual to guide the basic methods of speech analysis and extraction of fundamental frequency and so the basic operation Platform: |
Size: 5308416 |
Author:李璇玑 |
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Description: 当把m个信号叠加在一起时，经倒谱分析是能检测出其基频。但倒谱分析主要是用在同态滤波中，可用于某些信号的解褶积。例如提供的语音信号，就能通过倒谱把频谱中的包络和基频频谱分离，-When the m signal superimposed together, by the cepstrum analysis is able to detect its fundamental frequency. However, cepstral analysis is mainly used in homomorphic filtering can be used for the solution of certain signal deconvolution. Such as the provision of the speech signal, we can through the spectrum of cepstral envelope and baseband frequency spectrum separation Platform: |
Size: 1024 |
Author:小单 |
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Description: 语音信号的特征提取，语音信号的Mel倒谱特征（MFCC）的求解方法，语音信号的线性预测原理以及LPC特征的求解方法
-Speech signal feature extraction, speech signal characteristics of Mel cepstrum (MFCC) the solution, voice signals, as well as the principle of linear prediction characteristics of the LPC method Platform: |
Size: 366592 |
Author:孟星 |
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Description: Based on short-term energy detection and short-term cross zero rates detection in speech
reorganization,the paper presents two-threshold endpoint detection.In addition,an accurate speech
segmentation algorithm is achieved with the wavelet transform and statistics signal frequency domain
characteristics.using cepstrum transform and cepstrum distance with the background noise,the paper achieved
the speech segmentation algorithm.Analysis and Implementation of Speech Endpoint Detection Platform: |
Size: 413696 |
Author:读宴宾 |
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Description: 美国德克萨斯州大学电子工程系开发的一套进行语音分析的MATLAB程序．包括时域分析，语谱图分析，基频分析，共振峰检测等。对于语音分析会有很大的帮助-United States Department of Electronic Engineering, University of Texas developed a voice analysis of the MATLAB program. Including time-domain analysis, language spectrum analysis, frequency analysis, detection, etc. resonance peak. For speech analysis will be of great help Platform: |
Size: 380928 |
Author:feng |
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Description: 录制一段个人自己的语音信号。对录制的信号进行采样；画出采样后语音信号的时域波形和频谱图；对语音信号进行加噪和去噪处理，画出滤波后信号的时域波形和频谱，并对滤波前后的信号进行对比，分析信号的变化；回放语音信号；实现快录慢放、慢录快放等功能。-Record a person' s own voice signal. Of the recorded signal sampling draw sample after the speech signal time-domain waveform and frequency spectrum of voice signals, noise and de-noising processing, draw Filtered time-domain signal waveform and spectrum, and filtering the signal before and after comparative analysis of signal changes playback voice signal realize quickly recorded slow release, slow release recorded faster functions. Platform: |
Size: 243712 |
Author:或或 |
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Description: 定点频域ICA，使用高斯函数、负熵最大化来处理语音信号分离问题的演示-FIXED-POINT FREQUENCY DOMAIN ICA with
GENERALIZED GAUSSIAN FUNCTION BASED
NEGENTROPY APPROXIMATION for SPEECH SIGNAL
SEPARATION Platform: |
Size: 847872 |
Author:leo |
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Description: 基于小波变换的语音基频提取新算法，基于小波变换的语音基频提取新算法-Based on wavelet transform new algorithm for speech fundamental frequency extraction based on wavelet transform new algorithm for speech fundamental frequency extraction Platform: |
Size: 1298432 |
Author:dodogun |
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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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Search - frequency speech