Description: 建立了一种基于自组织神经网络的语音识别系统。对语音信号进行了预处理, 提取了语音信号的线性预测系数、线性预测倒谱系数和Mel 倒谱特征系数, 建立了基于自组织神经网络的识别判决模型.-Established a self-organizing neural network-based speech recognition system. Carried out on the speech signal pre-processing, extraction of the speech signal linear prediction coefficient, linear prediction cepstral coefficients and the characteristics of Mel cepstrum coefficient, based on self-organizing neural network model of identification judgments. Platform: |
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Author:张小天 |
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Description: 采用间接方法提取MEL倒谱，先计算自相关系数，然后由自相关系数计算LPC预测系数和反射系数，再计算LPC倒谱系数，最后由LPC倒谱系数计算MFCC 。-Indirect method of extracting MEL cepstrum, first calculating the autocorrelation coefficient, and then auto-correlation coefficient calculated by the LPC prediction coefficient and reflection coefficient, and then calculating the LPC cepstral coefficients, and finally by the LPC cepstral coefficient calculating MFCC. Platform: |
Size: 4114432 |
Author:大夹馅 |
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Description: MFCC (Mel Frequent Cepstral Coefficient) in M-File.
epresentation of the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency.
MFCCs derived as follows:
1. Take the Fourier transform of (a windowed excerpt of) a signal.
2. Map the powers of the spectrum obtained above onto the mel scale, using triangular overlapping windows.
3. Take the logs of the powers at each of the mel frequencies.
4. Take the discrete cosine transform of the list of mel log powers, as if it were a signal.
5. The MFCCs are the amplitudes of the resulting spectrum.
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Author:Mitha |
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Description: In this project we have processed the speech signal with the help of the DIGITAL SIGNAL PROCESSING techniques. The speech signal is given as the input will be verified using speech recognition technique using matlab. We have used Mel Frequency Cepstral Coefficient (MFCC) along with Vector Quantization (VQLBG) and Euclidean Distance to identify different characters. Based on the results, data was send to Parallel Printer Port of the computer & using relay different devices will be controlled.
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Size: 2048 |
Author:SimonKap22 |
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Description: VQ声纹识别算法和实验.
摘要：采用线性预测倒谱系数(1inear prediction cepstrum coefficient，LPCC)作为语音的特征参数，矢量量化(vector quantity，VQ)方法进行模式匹配，探讨声纹识别以实现身份认证，并对此识别方法进行了相关的实验．通过验证，这种方法可以区分不同的说话人，并且在做说话人辨认实验时可达到较高的识别率．-VQ pattern recognition algorithms and experimental sound. Abstract: The linear prediction cepstral coefficients (1inear prediction cepstrum coefficient, LPCC) as the voice of the characteristic parameters, vector quantization (vector quantity, VQ) method of pattern matching, pattern recognition of sound in order to achieve authentication and identification methods relevant to this experiment. Validated, this method can distinguish between different speaker, and speaker identification experiments to do to reach a higher recognition rate. Platform: |
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Author:海边贝壳 |
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Description: 语音识别MFCC特征提取matlab代码。 「梅尔倒频谱系数」（Mel-scale Frequency Cepstral Coefficients，简称MFCC），是最常用到的语音特征，此参数考虑到人耳对不同频率的感受程度，因此特别适合用在语音辨识。-Speech recognition MFCC feature extraction matlab code. \ Mel cepstrum coefficient (Mel- scale Frequency Cepstral Coefficients, MFCC), is the most commonly used to the phonetic characteristics of this parameter given ear to the feelings of different frequencies, so especially suitable for use in speech recognition Platform: |
Size: 1024 |
Author:Katherine |
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Description: 用MATLAB编写的语音信号的短时分析，主要包括：分帧、短时能量、短时平均幅度、短时过零率、temp函数、短时幅度差、倒谱、复倒谱temp1系数计等，是我多年调试通过的程序
-MATLAB prepared with short-term analysis of the speech signal, including: framing, short-time energy, short-term average amplitude, short-term zero rate, temp function, short-term amplitude difference, cepstrum, cepstral temp1 coefficient meter, etc. , is a program debugging through my years of Platform: |
Size: 4096 |
Author:c12imr |
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Description: 用MATLAB编写的语音信号的短时分析，主要包括：分帧、短时能量、短时平均幅度、短时过零率、 Swjqlf函数、短时幅度差、倒谱、复倒谱 mSfcKbB系数计等，是我多年调试通过的程序
-MATLAB prepared with short-term analysis of the speech signal, including: framing, short-time energy, short-term average amplitude, short-term zero rate,Swjqlf function, short-term amplitude difference, cepstrum, cepstral mSfcKbB coefficient meter, etc. , is a program debugging through my years of
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Size: 5120 |
Author:2e1pme |
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Description: 用MATLAB编写的语音信号的短时分析，主要包括：分帧、短时能量、短时平均幅度、短时过零率、 KPuiyk函数、短时幅度差、倒谱、复倒谱 rbUgYfE系数计等，是我多年调试通过的程序
-MATLAB prepared with short-term analysis of the speech signal, including: framing, short-time energy, short-term average amplitude, short-term zero rate,KPuiyk function, short-term amplitude difference, cepstrum, cepstral rbUgYfE coefficient meter, etc. , is a program debugging through my years of
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Size: 7168 |
Author:iigkh8 |
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Description: 用MATLAB编写的语音信号的短时分析，主要包括：分帧、短时能量、短时平均幅度、短时过零率、 olpjad函数、短时幅度差、倒谱、复倒谱 OkrzXPY系数计等，是我多年调试通过的程序
-MATLAB prepared with short-term analysis of the speech signal, including: framing, short-time energy, short-term average amplitude, short-term zero rate,olpjad function, short-term amplitude difference, cepstrum, cepstral OkrzXPY coefficient meter, etc. , is a program debugging through my years of
Platform: |
Size: 10240 |
Author:aae32b |
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