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STOCHASTIC MODELING BASED SPEECH RECOGNITION USING MFCC

Shodhganga@INFLIBNET

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Title STOCHASTIC MODELING BASED SPEECH RECOGNITION USING MFCC
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Contributor Abdul Mobin
 
Subject Artificial Neural Network; Dynamic Time Warping; Voice activation detection.
 
Description The aim is to recognize, compare,
newlineclassify and identify with the help of computation and applied techniques. To perform
newlinethe task of classification of noise sources, LPC and MFCC were used as input to the
newlineclassifiers in experimental work. LDA, QDA and ANN are tested for the classification
newlinepurpose. Once the source is identified we can address these untoward noisiness class
newlineand to minimize their impact to the human perceptions through the implementation of
newlineappropriate technique/devices to enhance the system recognition efficiency. The
newlineperformance of LDA, QDA and ANN with LPC and MFCC is analyzed. It is evident that
newlineANN in combination with MFCC gives the best result and showing efficiency about
newline90%.
newline
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Date 2018-10-04T05:15:58Z
2018-10-04T05:15:58Z
2010
2017
2018
 
Type Ph.D.
 
Identifier http://hdl.handle.net/10603/218344
 
Language English
 
Relation —
 
Rights university
 
Format —
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DVD
 
Coverage —
 
Publisher Delhi
Jamia Hamdard University
Department of Computer Science
 
Source University