Female speech is higher than male speech - Digital Signal Processing Design Experiment Final Report (2016).docx

8/17/2019 Female speech is higher than male speech - Digital Signal Processing Design Experiment Final Report (2016).docx

1/18

DESIGN EXPERIMENT TO SHOW THAT FEMALE VOICE

SPEECH IS HIGHER THAN MALE VOICE SPEECH

SIKSHA ‘O’

ANUSANDH AN

UNIVERSITY

(DEPARTMENT OF ELECTRONICS &

COMMUNICATION ENGINEERING)

SUPERVISED BY: DR. BADRINARAYAN SAHU

SUBMITTED BY:

SHUBHAM SARKAR - 1341016236

ANANYA PRADHAN - 1341016285

SHIBANEE BHUJABAL - 1341016063

BARADA PRASANNA MISHRA - 1341016106

BRANCH: ELECTRONICS AND COMMUNICATION ENGINEERING

SECTION: B

SUBJECT: DIGITAL SIGNAL PROCESSING !EC301P"

SEMESTER: 6TH

ACKNOWLEDGEMENT


2/18

I have conducted this design experiment report under the dynamic and

able guidance of our DSP (Digital Signal Processing) lecturer Dr.

Badrinarayan Sahu who had constantly encouraged helped me while

wor!ing on this report by providing valuable suggestions and instructions.

"he same is happening with me when I am desperately searching words to

than! the lab teachers for their guidance which helped me to bring out

this report wor! in uni#ue form.

$astly% I wish to express my sincere gratitude to my friends for their

constant encouragement and support.

----------------------------

Student’s Sin!tu"e


3/18

CONTENTS

S#$

N%$ "itle Page &o. 'emar!s

. Problem Statement

. 'esponse *ariable

+. ,hoice -f actors

/. Performing "he 0xperiment

Bloc! Diagram

12"$2B ,ode

/

3. 2nalysis

4aveforms

'esult

5

6. -bservation "ables 7

5. ,onclusion 8

9. 'eference ,itations 8


4/18

P"%#e' St!te'ent

Design an experiment to show that female voice speech is higher than male voicespeech.

Res%nse *!"i!#e

Speech re#uency

C+%i,e % F!,t%"s

.$ F"!'in

In order not to lose all time information in the transition to fre#uency domain% smallsections of the signal of about 7:/7 ms are treated one at a time so that the individualspectrum can be observed and the fundamental fre#uency can be calculated. "hesesmall sections are called frames$ 2nd the process of dividing the input speech signal intosmall frames of desired time slots is called framing.

/$ Wind%0in

1ost digital signals are in;nite% or su ?rectwin : 'ectangular window.


5/18

?bartlett : Bartlett window.

?hann : @ann window.

?hamming : @amming window.

?blac!man : Blac!man window.

T1es % Wind%0s

a. 'ectangular window>

"he rectangular window (sometimes !nown as the Boxcar or Dirchlet window) is the

simplest window% e#uivalent to replacing all but N values of a data se#uence by =eros%

ma!ing it appear as though the waveform suddenly turns on and oA.

"he rectangular window is the st order B:spline window as well as 7th power

cosine window$

b. Bartlett window>

Bartlett window is a window where L can be N% N% or N:. It is one type of triangular

window. 2ll three de;nitions converge at large N.

"he Bartlett window is the nd order B:spline window and can be seen as the

convolution of two &C width rectangular windows. "he ourier transform of the result is

the s#uared values of the transform of the half:width rectangular window.

c. @anning (@ann) window>

"he @ann window named after ulius von @ann and also !nown as the 2!nnin (for

being similar in name and form to the @amming window)% 3%n 2!nn and the "!ised

,%sine 0ind%0 is de;ned by (with hav for the haversine function).

"he ends of the cosine Eust touch =ero% so the side:lobes roll oA at about 5 dB per

octave.

d. @amming window>


6/18

"he window with these particular coe


7/18

In signal processing% the above de;nition is often used without the normali=ation% that is%

without subtracting the mean and dividing by the variance. 4hen the autocorrelation

function is normali=ed by mean and variance% it is sometimes referred to as the

!ut%,%""e#!ti%n ,%e5,ient.

iven a signal f(t)% the continuous autocorrelation is most often de;ned as thecontinuous cross:correlation integral of f(t) with itself% at lag .

2. Cest"u',epstrum analysis is a nonlinear signal processing techni#ue with a variety of

applications in areas such as speech and image processing. ,epstrum analysis is

concerned with the deconvolution of two signal types> the fundamental (basic) wavelet

and a train of impulses (excitation function). "he composite signal can be represented in

terms of power. ,omplex or phase cepstra.

!$ P%0e" Cest"u'

"he power cepstrum was de;ned in a 93+ paper by Bogert et al."he power cepstrum

of a signal is de;ned as the s#uared magnitude of the inverse ourier transform of the

logarithm of the s#uared magnitude of the ourier transform of a signal.

Power cepstrum of signal

$ C%'#e4 Cest"u'

"he complex cepstrum was de;ned by -ppenheim in his development of

homomorphic system theory and is de;ned as the Inverse ourier transform of the

logarithm (with unwrapped phase) of the ourier transform of the signal. "his is

sometimes called the spectrum of a spectrum.

,omplex cepstrum of signal F I"(log("(the signal)) Jm)(4here% m is the integer re#uired to properly unwrap the angle or imaginary part of the complex log function).

6#%,7 Di!"!'

/

INPUT SPEEC2

PRE-PROCESSING

FRAMING

WINDOWING

AUTO CORRELATION


8/18

MATLA6 C%de

(SOFTWARE USED MATLA6 R/8..!)

%program for finding the fundamental frequency

clc;

close all;

clear all;

l=input('Choose voice \n 1.Male voice .!emale voice\n'";

#=input('Choose frame \n 1.1$ms .ms &.&ms \n'";=input('Choose type of indo \n 1.)amming .)anning &.*ectangular

+.,lac#man $.,artlett\n'";

i=input('Choose the type of method \n 1.-utocorrelation .Comple/

cepstrum\n'";

%upload the speech signal

if l==1

0/fsn2its3=avread('456 Male voice.av'";%read av file for male

else

0/fsn2its3=avread('456 !emale voice.av'";%read av file for female

end

left=/(71"; % 8eft channel

% sound(/ fs";

fprintf('4uration = %g seconds\n' length(/"9fs";fprintf('5ampling rate = %g samples9second\n' fs";

fprintf(',it resolution = %g 2its9sample\n' n2its";

% plot aveform

t=(17length(/""9fs; % times of sampling instants

su2plot(11";

plot(t/:g:";

/la2el('


9/18

%for different type of indoing

if ==1

indo=hamming(8";

elseif ==

indo=hann(8";

elseif ==&

indo=rectin(8";elseif ==+

indo=2lac#man(8";

elseif ==$

indo=2artlett(8";

end

nooverlap=floor(89";%no of points after hich the indo repeats itself

nff = ma/($Dne/tpo(8"";

05 ! 63= spectrogram(Aindonooverlapnfffs'ya/is'";

%/tract the segment from .1 to .&$ seconds for analysis

if #==1 %for 1$ms

dt = 19fs;


10/18

hold on

plot(trng(


11/18

Resu#t

Inut-C+%%se 3%i,e.$M!#e 3%i,e /$Fe'!#e 3%i,e.C+%%se "!'e

.$.;'s /$/8's


12/18

Bit resolution = 16 bits/sample

F0 estimate is 306.2 "#.

Ose"3!ti%n T!#es

C!se-. -bservations for frame of 8ms.

T!#e-. Ksing @amming 4indow cepstrum method

M!#eF"e>uen,1

(2?)

Fe'!#eF"e>uen,1

(2?)

Ide!# M!#eF"e>uen,1

(2?)

Ide!# Fe'!#eF"e>uen,1

(2?)

C%'!"is%n

.8@$uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

/B=$;/ /B@$8; ./8 /.8 /B@$8;/B=$;

/

T!#e-uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.8@$uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

/B=$;/ /B@$8; ./8 /.8 /B@$8;/B=$;

/

9


13/18

T!#e-; Ksing Bartlett 4indow cepstrum method

M!#e

F"e>uen,1

(2?)

Fe'!#e

F"e>uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.@$8; =/=$8= ./8 /.8 =/=$8=.@$8;

T!#e- Ksing Bartlett 4indow autocorrelation method

M!#e

F"e>uen,1

(2?)

Fe'!#e

F"e>uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

/B=$;/ /B@$8; ./8 /.8 /B@$8;/B=$;/

T!#e-@ Ksing 'ectangular 4indow cepstrum method

M!#e

F"e>uen,1

(2?)

Fe'!#e

F"e>uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

/B=$;/ /B@$8; ./8 /.8 /B@$8;/B=$;

/

T!#e- Ksing Blac!man 4indow cepstrum method

M!#e

F"e>uen,1

(2?)

Fe'!#e

F"e>uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

=@$


14/18

F"e>uen,1

(2?)

F"e>uen,1

(2?)

F"e>uen,1

(2?)

F"e>uen,1

(2?)/B=$;/ /B@$8; ./8 /.8 /B@$8;/B=$;

/

C!se-/ -bservations for frame of 7ms.

T!#e-. Ksing @amming 4indow cepstrum method

M!#e

F"e>uen,1

(2?)

Fe'!#e

F"e>uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

=;$uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

/.8$8 uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.@$8; =;$uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

/.8$8 uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n


15/18

.@$8; =;$uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

/.8$8 uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

uen,1(2?)

Ide!# Fe'!#e

F"e>uen,1(2?)

C%'!"is%n

/.8$8 uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.@$8; =/=$8= ./8 /.8 =/=$8=.@$8

;

T!#e-.8 Ksing Blac!man 4indow autocorrelation method

M!#e

F"e>uen,1

(2?)

Fe'!#e

F"e>uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

/.8$8


16/18

C!se-uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.@$8; =/=$8= ./8 /.8 =/=$8=.@$8

;

T!#e-/ Ksing @amming 4indow autocorrelation method

M!#e

F"e>uen,1

(2?)

Fe'!#e

F"e>uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

=/=$8= ;.8$


17/18

F"e>uen,1

(2?)

F"e>uen,1

(2?)

F"e>uen,1

(2?)

F"e>uen,1

(2?).uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

=8$88 ;.8$uen,1

(2?)

Ide!# M!#e

F"e>uen,1

(2?)

Ide!# Fe'!#e

F"e>uen,1

(2?)

C%'!"is%n

.


18/18

techni#ues% the value of the fre#uency for female speech was higher than that of themale speech. Similarly% for the frame time of 7ms and +7ms% it was observed that thefre#uency of female speech was higher than that of the male speech for diAerentwindowing techni#ues.

4e also observed that the hamming windowing techni#ue for the frame time of +7ms

gives us the best result.

"hus% we can conclude from the above +7 observations that t+e "e>uen,1 e'!#e3%i,e see,+ is +i+e" t+!n t+e '!#e 3%i,e see,+$

Ree"en,e & Cit!ti%ns

I$ We Lin7s-.$ 000$'!t+0%"7s$,%'/$ 000$st!,7%3e"%0$,%'

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Female speech is higher than male speech - Digital Signal Processing Design Experiment Final Report (2016).docx