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Description: 求mel频率倒谱系数的matlab程序-for mel frequency cepstrum coefficients of Matlab procedures
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Size: 2048 |
Author: wh |
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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
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Size: 165888 |
Author: xiang |
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Description: 语音处理中用于特征提取，mel倒谱系数法可以反映语音的动态特征。-Voice processing for feature extraction, mel cepstral coefficients method can reflect the dynamic characteristics of voice.
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Size: 4096 |
Author: 方方 |
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Description: mfcc mel倒谱系数学习。适合语音识别参数的学习。-mfcc mel cepstral coefficient learning. Parameters for speech recognition learning.
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Size: 1024 |
Author: 沈立金 |
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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.
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Size: 114688 |
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.
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Size: 4114432 |
Author: 大夹馅 |
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Description: 可以在CCS中运行的LPCC程序，包括语音参数分析主函数，信号的自相关函数，由自相关函数计算LPC预测系数，由LPC预测系数计算LPC倒谱系数，由LPC预测系数计算MEl到普系数等函数-CCS can be run at the LPCC procedures, including analysis of voice parameters of the main function, the signal autocorrelation function, autocorrelation function calculated from LPC prediction coefficients, by the LPC prediction coefficients LPC cepstral coefficients, calculated by the LPC prediction coefficients to the S & P coefficients Mel such as function
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Size: 3072 |
Author: renmay |
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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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Size: 1024 |
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: 从说话人的语音信号中提取说话人的个性特征是声纹识别的关键。主要介绍语音信号特征提取方法中的Mel倒谱系数
-From the speaker s voice signal to extract the speaker s personality traits is the key to Voiceprint identification. Mainly introduces the speech signal feature extraction method in Mel cepstral coefficients
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Size: 241664 |
Author: 于高 |
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Description: OTOMATİ K KONUŞ MA TANIMA ALGORİ TMALARININ UYGULAMALARI
Kö ksal Ö CAL
Ankara Ü niversitesi
Fen Bilimleri Enstitüsü
Elektronik Mühendisliğ i Anabilim Dalı
Danı ş man : Yrd. Doç . Dr. H. Gö khan İ LK
Bu ç alı ş mada, SMM (Saklı Markov Model) tabanlı izole bir kelime tanı ma sistemi geliş tirilerek, sesin akustik parametreleri LPC (Linear Predictive Coding), LPCC (LPC Cepstrum), CEPS (Ayrı k Fourier dö nüş ümü tabanlı cepstrum) ve MFCC (Mel Frequency Cepstral Coefficients) ‘nin konuş macı dan bağ ı msı z konuş ma tanı ma sistemlerindeki performansları değ erlendirilmiş tir. Değ iş ik akustik parametrelerle birlikte değ iş ik S-OTOMATİ K KONUŞ MA TANIMA ALGORİ TMALARININ UYGULAMALARI
Kö ksal Ö CAL
Ankara Ü niversitesi
Fen Bilimleri Enstitüsü
Elektronik Mühendisliğ i Anabilim Dalı
Danı ş man : Yrd. Doç . Dr. H. Gö khan İ LK
Bu ç alı ş mada, SMM (Saklı Markov Model) tabanlı izole bir kelime tanı ma sistemi geliş tirilerek, sesin akustik parametreleri LPC (Linear Predictive Coding), LPCC (LPC Cepstrum), CEPS (Ayrı k Fourier dö nüş ümü tabanlı cepstrum) ve MFCC (Mel Frequency Cepstral Coefficients) ‘nin konuş macı dan bağ ı msı z konuş ma tanı ma sistemlerindeki performansları değ erlendirilmiş tir. Değ iş ik akustik parametrelerle birlikte değ iş ik SMM
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Size: 1241088 |
Author: strike |
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Description: 这个函数也要被melcepst函数调用，用来进行计算Mel倒谱系数。这个函数的作用是构造mel滤波器组。-This function must be melcepst function call is used to calculate Mel cepstral coefficients. The role of this function is to construct a mel filter bank.
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Size: 2048 |
Author: bradden |
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Description: 音频mfcc 参数计算 用于计算语音信号的Mel倒谱系数-Audio mfcc parameter calculation used to calculate the speech signal Mel cepstral
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Size: 4096 |
Author: kong |
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Description: MFCC algorithm for calculating mel frequenc cepstral coefficients.
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Size: 3072 |
Author: sid |
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Description: Speech Recognition using MEL cepstral Coefficients
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Size: 3072 |
Author: ab.m |
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Description: 语音信号的时域频域分析，从短时能量到语谱图，以及线性预测参数和梅尔倒谱系数-Speech signal in time domain frequency domain analysis, from the short-term energy to the spectrogram, and the linear prediction parameters and the Mel cepstral coefficients, etc.
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Size: 747520 |
Author: 菁菁 |
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Description: MEL FREQUENCY CEPSTRAL COEFFCIENT
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Size: 3072 |
Author: seo wan |
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Description: This project describes the work done on the development of an audio segmentation and classification system. Many existing works on audio classification deal with the problem of classifying known homogeneous audio segments. In this work, audio recordings are divided into acoustically similar regions and classified into basic audio types such as speech, music or silence. Audio features used in this project include Mel Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate and Short Term Energy (STE). These features were extracted from audio files that were stored in a WAV format. Possible use of features, which are extracted directly from MPEG audio files, is also considered. Statistical based methods are used to segment and classify audio signals using these features. The classification methods used include the General Mixture Model (GMM) and the k- Nearest Neighbour (k-NN) algorithms. It is shown that the system implemented achieves an accuracy rate of more than 95 for discrete audio classification.-This project describes the work done on the development of an audio segmentation and classification system. Many existing works on audio classification deal with the problem of classifying known homogeneous audio segments. In this work, audio recordings are divided into acoustically similar regions and classified into basic audio types such as speech, music or silence. Audio features used in this project include Mel Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate and Short Term Energy (STE). These features were extracted from audio files that were stored in a WAV format. Possible use of features, which are extracted directly from MPEG audio files, is also considered. Statistical based methods are used to segment and classify audio signals using these features. The classification methods used include the General Mixture Model (GMM) and the k- Nearest Neighbour (k-NN) algorithms. It is shown that the system implemented achieves an accuracy rate of more than 95 for discrete audio classification.
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Size: 653312 |
Author: kvga |
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Description: hidden markov model based text to speech
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Size: 116736 |
Author: manjong |
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Description: 应用matlab实现梅尔倒谱系数的提取，通过采用不同样本进行数据对比-Application matlab realize extract Mel cepstral pedigree data by comparing different samples
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Size: 135168 |
Author: 张宁 |
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