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Description: classification algorithm among Unvoiced/voiced speech and silence
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Size: 622592 |
Author: JP |
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Description: dereverberator code for matlab using voiced-unvoiced classification of speech signals
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Size: 6144 |
Author: clase |
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Description: Separation of voiced and unvoiced portions using Zero crossing rate ans energy
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Size: 210944 |
Author: pravin |
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Description: 自相关虽然能够判断清/浊音，并估计浊音的基音周期，但是其运算量很大，用乘法运算所需时间较长。为了避免乘法，采用短时平均幅度差函数（AMDF），验证AMDF与自相关有类似的作用，即平均幅度差函数能够代替自相关函数进行语音分析。-Although autocorrelation can differ from the Voiced/Unvoiced and voiced the pitch period estimate, but the operation is large enough, with the multiplication time was needed. In order to avoid the multiplication using the short time average magnitude difference function (AMDF), verify the AMDF and autocorrelation have a similar effect, that the average magnitude difference function can replace the voice of the autocorrelation function.
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Size: 20480 |
Author: 吴艳花 |
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Description: Usually, speaker recognition systems do not take into account the short–term dependence between the vocal source and the vocal tract. A feasibility study that retains this dependence is presented here. A model of joint probability functions of the pitch and the feature vectors is proposed. Three strategies are designed and compared for all female speakers taken from the SPIDRE corpus.
The fi rst operates on all voiced and unvoiced speech segments (baseline strategy). The second strategy considers only the voiced speech segments and the last includes the short–term pitch information along with the standard MFCC. We use two pattern recognizers: LVQ–SLP and GMM. In all cases, we observe an increase in the identifi cation rates and more specifi cally when using a time duration of 500 ms (6 higher).-Usually, speaker recognition systems do not take into account the short–term dependence between the vocal source and the vocal tract. A feasibility study that retains this dependence is presented here. A model of joint probability functions of the pitch and the feature vectors is proposed. Three strategies are designed and compared for all female speakers taken from the SPIDRE corpus.
The fi rst operates on all voiced and unvoiced speech segments (baseline strategy). The second strategy considers only the voiced speech segments and the last includes the short–term pitch information along with the standard MFCC. We use two pattern recognizers: LVQ–SLP and GMM. In all cases, we observe an increase in the identifi cation rates and more specifi cally when using a time duration of 500 ms (6 higher).
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Size: 93184 |
Author: morteza |
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Description: Wavelet based voiced/unvoiced classification algorithm
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Size: 1196032 |
Author: sara |
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Description: 语音信号处理短时分析的实验以实验报告，处理有语音信号的短时幅值、自相关函数、短时能量和分辨清音和浊音-The analysis of the short speech signal processing experiments to test report, with the short speech signal amplitude, the autocorrelation function, short-term energy and distinguish the voiced and unvoiced speech
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Size: 778240 |
Author: xiaoxiami365 |
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Description: 基于matlab软件,的语音清音帧和浊音帧进行线性分析。-Based on the MATLAB software,on speech unvoiced frames and voiced frame using linear prediction analysis,respectively.
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Size: 1024 |
Author: 王涛 |
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Description: Matlab code for doing Voiced Unvoiced and Silence Classification in a speech signal
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Size: 4096 |
Author: Parvathy |
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Description: 对语音清音和浊音的区别，主要利用的是矩形窗，自相关处理-Voice unvoiced and voiced distinction, the main advantage is that the rectangular window, the autocorrelation processing
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Size: 3072 |
Author: 徐吴 |
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Description: end point detection or silence removal i.e to remove voiced or unvoiced speech
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Size: 1024 |
Author: aaron |
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Description: 实现清音与浊音的频谱分析，通过加不同窗，分析清音和浊音频谱变化-Unvoiced and voiced spectral analysis, analysis of unvoiced and voiced spectral variation, by adding different window
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Size: 1024 |
Author: 李希 |
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Description: separates the voiced and unvoiced portion and performs STFT
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Size: 88064 |
Author: Kriti Chhabra |
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Description: 一个基于遗传算法与mp的外文文献，讲的很清楚明了，有参考价值-VOICED/UNVOICED SPEECH DISCRIMINATION IN NOISE USING GABORATOMIC DECOMPOSITION
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Size: 59392 |
Author: 王一 |
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Description: VOICE UNVOICED SILENCE PITCH MARKING-VOICE UNVOICED SILENCE PITCH MARKING
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Size: 3072 |
Author: GWMSART BASUMATARY |
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Description: to find zero crossing rate of speech signal to distinguish between voiced and unvoiced signal
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Size: 258048 |
Author: preet |
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Description: finding energy of speech signal to distinguish between voiced and unvoiced signal
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Size: 258048 |
Author: preet |
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Description: Short Term Energy is important for filtering a signal.
With Short Term Energy, we can get voiced and unvoiced.
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Size: 33792 |
Author: Chusnul |
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Description: Splice out the voiced plosive “b” in theword “be” and synthesize aword with an increase in the
voice onset time of the “b.” What is the perceptual effect? Is it possible to transform the voiced
plosive “b” to the unvoiced plosive “p” with this change in the voiced onset time? Consider
attributes such as vocal cord vibration and aspiration. (In splicing, display the waveform and
spectrogram of the word “be” and use the MATLAB function ginput.m.) Optional: If your
transformed sound does not sound like a “p” then, again considering vocal cord vibration and
aspiration, make a more accurate transformation.
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Size: 1024 |
Author: asdamha |
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Description: 自动估测语音信号的基音频率。目前只能估计浊音，清音没有基音周期（会报错），基音周期取第二、三帧及以后的帧数。003和191分别是男声和女声的语音信号包。-Automatic estimation of the pitch frequency of the speech signal. Currently only estimated voiced, unvoiced no pitch (being given), take the second pitch, and after three frames. 003 and 191 are male and female voice signal packets.
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Size: 138240 |
Author: jack |
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