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A Study of Noise Reduction in Speech Signal

using FIR Filtering

Supavit Muangjaroen andThaweesak YingthawornsukAbstract-FIR filter has been designed to have impulse

responses associated with the cut-off frequencies at 0.75 KHz,

1KHz, 1.25KHz and 1.5 KHz. The randomized noisespurposely used in signal corruption with input speech signal

are generated by Matlab program. Signal comparison betweenfiltered speech and original speech signal shows that estimated

MSE values in all cut-off frequencies are decreasing similarly,suggesting FIR filters can effectively retrieve the desired

speech signal from noise corruption.

Keywords-Filter, FIR, Noise, Impulse Response.

I. INTRODUCTION

HIS paper presents the study of noise filtering and

its efficiency of eliminating noise interference on

corrupted speech signal regarding the acoustical quality

in spoken word recording which has to be fairly treated

prior to processing stage, when the purposed task

involves with speech processing in analysis. Results and

outcomes can be diversified due to noise corruption in

speech signal by noise. Speech processing has been well

applied into various areas of technology such as

telephone banking, voice activation in vehicle, database

access service, word recognition, speaker verification,

emotional detection, assistive technology in emotionaldisorder diagnosis, and identification of vocal-related

illnesses.

Signal filter is most required for many tasks, which

can be considered into analog and digital filters. Most

analog filters are designed and implemented as

electronic circuit which is a lump of electronic and

electrical components. This type of filter is generally

more expensive and more difficult to design in terms of

circuit assembly, testing, and final modification. Filter is

one of the most important parts of electronic circuit

when it is designed to deal with signal processing

directly and indirectly in some circumstances as well.

In this work the digital filter is purposely considered

and studied due to its advantages in high stability,frequency deviation range, computer based design, low-

cost implementation, and more reliability compared to

analog filter.

Supavit Muangjaroen is with Department of Electrical TechnologyEducation, King Mongkut's University of Technology Thonburi,

Thailand

Thaweesak Yingthawornsuk is with Department of MediaTechnology and Department of Electrical Technology Education, King

Mongkut's University of Technology Thonburi, Thailand

Digital filters can be generally classified into two

major types regarding the time interval of impulse

response of filter system, which are Finite Impulse

Response (FIR) and Infinite Impulse Response (IIR) [1].

Impulse responses of these filters are shown in Figure 1.

Based on less complicated design and implementation

corresponding the required tasks for FIR filter, it has

been more popularly used due to providing more stable

frequency response in terms of sharpness of cut-off

frequency edge and low ripple than IIR filter. Therefore,

our main objectives of this study are focused on the

experimental design of FIR filtering, testing andevaluating on how efficient designed filter can eliminate

noise signal from the corrupted input signal at different

noise levels.

Fig. 1 Impulse responses of FIR and IIR filters [2].

II. WINDOW METHOD

The window method is used in design of filter toestimate the impulse response of filter corresponding to a

desired frequency bandwidth. Figure 2 shows four

common frequency responses of FIR filter generally

used in design. In this study, a low-pass FIR filter is

designed with a required cut-off frequency of 5 KHz and

300 Hz transition bandwidth and sampling frequency set

equal to 10 KHz which relates to the frequency response

of human speech signal. Most concentrated energy can

be found within frequency range of 0-5KHz or less than

that in some speaker.

Fig. 2 Frequency responses of ideal filters [2].

T

International Conference on Advances in Electrical and Electronics Engineering (ICAEEE'2012) April 13-15, 2012 Pattaya

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Fig. 7 Comp

signal and filt

Fig. 8 Comp

signal and filt

Fig. 9 Comp

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rison among or

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iginal speech si

t cut-off frequ

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at cut-offfrequ

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cut-offfreque

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nal, corrupted

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Fig. 10

signal andTo fin

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Fig. 13 Tende

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signal retriev

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Author w

Yingthaworn

ncies of MSE c

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higher than t

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IV. CON

tal results rev

ented by Ma

ise from dat

SE values s

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noise-free s

ACKNOW

ould like t

uk, Departm

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rious frequencie

rresponding torious frequencie

e MSE estimat

ith cut-off fro

own to the nof around 94

graph in Fi

starting appro

ise levels ge

11 and figure

matically dec

As compared

ese in figure

cessful for all

CLUSIONS

aled that the

tlab program

speech sign

ggest that t

ssing can can

peech signal

EDGEMENTthank Dr

nt of Medi

original speech

s.

noise corrupteds.

ed equal to 3.

m the 0.75-1.

oise reductio. Error values

ure 12 sho

imately at 28

tting low. Th

12 can be see

reasing near t

MSE values i

13, suggestin

designed FI

designed FIR

can eliminate

al effectively.

he FIR filter

cel noises and

after filtering

. Thaweesak

Technology

-

.

,

KMUTT,

design a

Electrical

laborator

[1].KucHill,

[2].TaylHill,

[3].Oppand

NJ:

[4].Mr.Tdigit

Finit

for valuabl

d discussion

Technology

facilities.

RR, Introduction

International Edit

r F.J., Principl

New York, 1994.

nheim, A. V., an

ystems. In: Digit

rentice-Hall, 197

anan , Mr.pamo

al filter (HPF), th

e Impulse Respon

e suggestion

on results,

ducation as

EFERENCES

to Digital Signal

ion, 1988.

s of Signals a

d R. W. Schafer.

alb signal Proces

, pp.6-44.

and Dr. Siri

impulse respons

se: FIR With MA

on experim

nd Departme

well for supp

Processing, Mc

nd Systems, Mc

Discrete-Time S

ing. Englewood

The design and

in a limited num

TLAB.

ental

nt of

rting

raw-

raw-

ignals

liffs,

test a

ber of


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