linear predictive cepstral coefficients
Vol 4, No 12 (2016)
... Abstract— In this paper, we introduced a text- depend speaker recognition by using wavelet transform under stressed conditions. Here we compare different feature such as ARC, LAR, LPCC, MFCC, CEP and after comparison we ...
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Analysis of Feature Extraction Methods for Speech Recognition
... scale cepstral coefficients, Perceptual linear prediction, linear predictive cepstral coefficients and linear predictive coding are the most proposed ...
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Analysing the Performance of Speaker Verification Task using Different Features
... tion coefficients ai is done by minimizing the prediction error ...prediction coefficients are then further transformed into Linear Predictive Cepstral Coefficients (LPCC) using ...
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EFFICIENT SCHEDULING OF WORKFLOW IN CLOUD ENVIORNMENT USING BILLING MODEL AWARE TASK CLUSTERING
... include linear predictive coefficients (LPC), linear predictive cepstral coefficients (LPCC) and Mel-frequency cepstral coefficients ...by linear ...
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Isolated English alphabet speech recognition using wavelet cepstral coefficients and neural network
... the Linear Predictive Coefficient (LPC), Linear Predictive Cepstral Coefficient (LPCC), and the MFCC shows high performance when used under benign conditions however, their performance ...
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Feature Extraction Methods based on Linear Predictive Coding and Mel Frequency Cepstral Coefficients for Recognizing Spoken Words in Assamese Language
... In order to obtain or designing an intelligent and accurate system for the automatic recognition of speech, feature extraction process is considered as the key and most important phase. There are different speech feature ...
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Hardware Implementation of Speech Recognition Using MFCC and Euclidean Distance
... recognition, Linear predictive coefficients (LPC) cepstrum based on LPC or Mel frequency Cepstral Coefficients (MFCC) are based on Mel-frequency filter bank are widely used as feature ...
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A Survey on Feature Extraction Algorithm for the Speech Recognition System
... Frequency Cepstral Coefficients (MFCC), Perceptual Linear Prediction (PLP), Linear Predictive Codes (LPC) are used for feature extraction in speech ...
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Automatic Recognition of Machinery Noise in the Working Environment
... Recognition of different sounds has a long history, with its roots in 1952 when Bell Labs demonstrated the first automatic speech recognition (ASR) systems for small-vocabulary recognition of digits spoken over the ...
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Comparison of Multidimensional MFCC Feature Vectors for Objective Assessment of Stuttered Disfluencies
... Perceptual linear prediction is based on the short-term spectrum of ...pure linear predictive analysis of speech, perceptual linear prediction modifies the short-term spectrum of the speech by ...
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A Review: Person Recognition Based on Humming
... Frequency Cepstral Coefficients (MFCC), Linear Predictive coefficients (LPC), Perceptual Linear Prediction (PLP) and all other feature vectors are used as an input to the ...
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Fet Small Signal Modelling Based on the Dst and Mel Frequency Cepstral Coefficients
... Abstract—In this paper, a new technique is proposed for field effect transistor (FET) small-signal modeling using neural networks. This technique is based on the combination of the Mel frequency cepstral ...
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Noise-Robust Speech Features Based on Cepstral Time Coefficients
... and the resultant matrix is called the cepstral time matrix (CTM) [6, 7]. After CTM for each frame is extracted, we further apply normalization and routines for delta and acceleration feature extraction to the ...
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Using Mel Frequency Cepstral Coefficients in Missing Data Technique
... Generally, cepstral features are more compactible, discriminable, and most importantly, nearly decorrelated such that they allow the diagonal covari- ance to be used by the hidden Markov models (HMMs) ef- ...to ...
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Improving of Feature Selection in Speech Emotion Recognition Based-on Hybrid Evolutionary Algorithms
... The feature extraction and selection can be known as the most important sections in speech emotion recognition due to the ambiguity of the effective features in emotion recognition and vocal diversity [2]. Feature ...
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A Comparative Study of Feature Extraction Techniques for Speech Recognition System
... Derived Cepstral Coefficients), Linear Prediction (LP, LP Derived Filer Bank Amplitudes, LP Derived Cepstral Coefficients) used in speech recognition ...
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Audio bandwidth extension based on temporal smoothing cepstral coefficients
... into cepstral coeffi- cients and propose a novel temporal smoothing cepstral coefficient (TSCC)-based scheme for BWE of audio ...and cepstral normalization. Finally, the extracted cepstral ...
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An Approach To Feature Selection Algorithm Based On Ant Colony Optimization For Human Emotion Recognition Using Speech
... Mel frequency scale represents subjective (perceived) pitch. It is one of the perceptually movtiated frequency scales (see figure above). Mel scale is constructed using pair wise comparisons of sinusoidal tones: a ...
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Mel Frequency Cepstral Coefficients Based Pattern Recognition for Limb Motor Action
... Fisher Linear Discriminant Analysis (FLDA):FLDA is a well-known linear classifier based on the Fisher ...data. Linear classifier projects multidimensional data into one dimension and we take decision ...
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Feature Extraction Techniques for Voice Operated PC Application
... 2. The experiments in human perception have shown that frequencies of a complex sound within a certain bandwidth of some nominal frequency cannot be individually identified unless one of the components of this sound ...
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