Novel Voice Ppt
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Transcript of Novel Voice Ppt
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DEVELOPMENT OF A NOVEL VOICE
VERIFICATION SYSTEM USINGWAVELETS
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AIM OF THE PROJECT
The aim of the project is to study The VoiceRecognition Using Wavelet FeatureExtraction employ wavelets in voicerecognition for studying the dynamicproperties and characteristics of the voice
signal .
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INTRODUCTION
The developed voice recognition system is wordindependant voice verification system combiningthe RASTA and LPC.
The voice signal is filtered using the specialpurpose voice signal filter using the RelativeSpectral Algorithm (RASTA)
The signals are denoised and decomposed toderive the wavelet coefficients and thereby astatistical computation is carried out.
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CONT....
the accuracy of the verifying sample individualvoice to his own voice is quite high (around 75%to 80%).The reliability of the signal verification isstrengthened by combining entailments fromthese two completely different aspectsof theindividual voice.
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CONT....
For voice comparison purposes four out fiveindividuals are verified and the results showhigher percentage of accuracy .The accuracy of the system can be improved byincorporating advanced pattern recognitiontechniques such as Hidden Markov Model(HMM).
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WAVELETS
Data
Time domain
Frequency domain
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FOURIER TRANSFORMS
The Great Father Fourier - Fourier Transforms
Any Periodic function can be expressed aslinear combination of basic trigonometricfunctions
(Basis functions used are sine and cosine )
df e f X t x
dt et x f X
ift
ift
2
2
)()(
)()(
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COSINE AND SINE PARTS
Real partand imaginary
part
)sin()cos(2 / )( 0 ft b ft aat x f f
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DRAWBACKS
Integration from -inf to +inf
Gives frequency content of total time series but temporalinformation is lost!
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SHORT TIME FOURIER TRANSFORMS
Same as usual Fourier transforms, but data is modified bymultiplication with a window functionOnly part of data at a time is taken and processed
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DRAWBACKS OF STFT
Frequency and time resolutions are fixed(Wider the window width, lesser the time resolutionand more the frequency resolution and vice versa)
As frequency resolution increases, timeresolution decreases uncertainty principle
Desired: Good time resolution at highfrequencies and good frequencyresolution at low frequencies!
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WHAT ARE WAVELETS?
A small waveExtends to finite interval
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SOME MATHEMATICAL EXPRESSIONS
dt s
t t x
ssW )(
1),(
x ( t ) actual time series(t) wavelet function
dt t
dt t
2)(
0)(
Integrable and limited to finiteregion
Total energy finite
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TYPICAL PICTURE
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1D WAVELET TRANSFORM
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RASTA (RELATIVE SPECTRAL ALGORITHM )
This method works by applying a band-pass filterto the energy in each frequency sub-band in orderto smooth over short-term noise variations and toremove any constant offset.stationary noises are often detected. Stationarynoises are noises that are present for the
fullperiod of a certain signal and does not havediminishing feature
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CONT..
The assumption that needs to bemade is that thenoise varies slowly with respect to speech.This makes the RASTA a perfect tool to beincluded in the initial stages of voice signalfiltering to remove stationary noisesThe stationary noises that are identified are noisesin the frequency range of 1Hz - 100Hz .
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SYSTEM IMPLEMENTATION
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RESULTS
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CONT...
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CONCLUSION
The Voice Recognition Using Wavelet FeatureExtraction employ wavelets in voice recognition forstudying the dynamic properties and characteristicsofthe voice signal. The voice recognition system that is
developed is word dependant voice verification systemused to verify the identity of an individual based ontheir own voice signal using the statistical computation,formant estimation and wavelet energy.. By using thefifty preloaded voice signals from five individuals, theverification tests have been carried and an accuracy rateof approximately 80 % has been achieved
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THANK YOU