This PPT presentation is based on the topic Speech Recognition using DWT
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DSP has its own functions in Mat lab for
Provides best quality of voice processing.
Offers various options like
Using Daubechies WT the signal is divided in to no of octaves.
Analyze the different octaves and the characteristic octave is found out.
Different characteristic properties are
magnitude of the amplitude
No of samples above a threshold level.
Templates are created for different spoken words.
Each time the input signal is compared with the templates.
Wavelets proves to be an effective method in analyzing speech signals that contain both steady state characteristics (vowels) and transient characteristics (consonants).
Better result can be got by finding even more differences in different octaves between each of the digits and adding formants and pitch determinations to the wavelet analysis.
Use of continuous wavelet transform which steps though the frequencies and times continuously.