1. SPEAKER IDENTIFICATION
SYSTEM WITH VOICE –
CONTROLLED
FUNCTIONALITY

2. Introduction
Objective  To develop a speaker identification
system and control the system using a person’s
voice.
Platform  Matlab
Implementation of Artificial Neural Networks
(ANN) for pattern classification
Feature extraction  MFCC
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3. Experimental Setup
Sound Recorder Feature Extraction
Speech Wav File MFCC
Artificial Neural Network Subsystem
Test Train
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4. Signal Processing
Built - in MATLAB function
‘wavrecord.m’
The recorded samples serve as input to
the next stage, which is the Mel –
Frequency Cepstral Analysis.
4

5. Feature Extraction
Mel – Frequency Cepstral Coefficients (MFCC)
MFCCs are based on the known variation of the
human ear’s critical bandwidths with frequency
Linear at low frequencies and logarithmic at high
frequencies
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6. MFCC Block Diagram
Speech Frame Frame Windowing FFT
Blocking
Mel Cepstrum Mel Mel–Freq. Spectrum
Cepstrum
Wrapping
Spectrum
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7. Steps of MFCC
1. Frame Blocking
2. Windowing
3. Fast Fourier Transform (FFT )
4. Mel–Frequency Wrapping
5. Cepstrum
Auditory Toolbox - mfcc.m
ceps=mfcc(input, sampling rate, [frame rate])
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8. Artificial Neural Networks (ANN)
General models of how human brain processes
information.
Layered architecture  Consists of nodes
corresponding to neurons and of weights
corresponding to connections between neurons
“Learning” rule  Weights are adjusted on the
basis of a series of training patterns
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9. Probabilistic Neural Network (PNN)
Feed – forward neural network
Provides a general technique to solve pattern classification
problems
Develops distribution function to estimate the likelihood of
an input pattern being within several given categories.
Created in MATLAB using ‘newpnn’
net = newpnn(p,t)
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10. Schematic Diagram
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11. Conclusion
Implementation difficult due to variability
in speech signal
Possible improvement using noise
cancellation techniques  Weiner Filter,
Adaptive Filters
11

12. References
L.Rabiner, B. H. Juang – Fundamentals of Speech
Recognition
C. P. Lim, S.C. Woo – Speech Recognition using
Neural Networks. IEEE Trans. on Acoustics,
Speech and Signal Processing - 2000.
Khalid Saeed and Mohammed Kheir Nammous –
A Speech and Speaker Identification System.
IEEE Trans. on Industrial Electronics - 2007.
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