PERPUSTAKAAN UMP
Ili III III III I IliI III III IllI 0000071447
SOUND CHARACTERISTICS FOR SWIFTLETS ATTRACTION
Sm NAL ZAINI BT HUSNI ZA1NI
This thesis is submitted as partial fulfillment of the requirements for the award of the
Bachelor of Electrical Engineering (Electronics)
Faculty of Electrical & Electronics Engineering
Universiti Malaysia Pahang
ilL, 2012
PERPUSTAPAAN 19/7 UNIVERSITI MALAYSIA PAHANG r
1 IL C fl.
No. Porolehan No. Panggilan
O1447 Tardth
L.q
08, MAR 2013
ABSTRACT
This project research about the analysis of sound can attract the swiftlets enter in
swiftiets house. This is because the main swiftiets character is attraction toward sound.
But the problem is doing not have any research to identify sound characteristic most are
swiftiets more attract. These are important use for industry to attract swiftiets enter and
build their nests in man-made house. In house fitted bird-call recording in cave to
attract attention bird go inside house to be doing nest. Therefore, this study shall be
analyzing sound features that there is in bird-call recording that has attracted attention
bird. The methpd that will be used is taking a few of sample of swiftiets sound for
analysis by using Matlab software. From analysis can identify sound characteristic
where can attrct swiftiets from analysis the signal. The expectation from this research
is can find sound characteristic for swiftlets attraction by analysis the frequency and
amplitude of noise sound and original sound.
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ABSTRAK
Kajian projek mi tentang analisis bunyi yang boleh menarik burung walet
memasuki rumah burung walet buatan manusia. Hal mi kerana, sifat utama burung
walet yang tertarik ke arah bunyi. Tetapi masalalmya ialah tiada sebarang kajian untuk
mengenal pasti ciri-ciri bunyi yang membuatkan burung itu tertarik untuk membuat
sarang burung di dalam rumah. Perkara mi penting kepada penggunaan industri untuk
menarik swiftiets memasuki dan membina sarang mereka dalam rumah buatan manusia
untuk tujuan pemiagaan. Rakaman kicauan burung dalam gua iaitu habitat semula jadi
burung walet untuk akan diletakkan di luar rumah untuk menarik perhatian burung
untuk masuk ke dalam rumah untuk membuat sarang. Jadi, kajian mi akan
menganalisis ciri-ciri bunyi yang terdapat dalam rakaman kicauan burung walet tersebut
yang menjadi penyebab burung walet tertarik terhadap bunyi tersebut. Kaedah yang
akan digunakan mengambil beberapa daripada sampel bunyi burung walet untuk
dianalisis dengan menggunakan perisian Matlab. Daripada analisis tersebut, kita boleh
mengenal pasti ciri- ciii bunyi yang terdapat pada rakaman tersebut dengan analisis
terhadap isyaiat yang dipercil1ii. Jangkaan dari penyelidikan mi ialah boleh melihat
analisis terhadap bunyi asal dan bunyi bising dari aspek frekuensi dan kekuatan bunyi.
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TABLE OF CONTENTS
CHAPTER TITLE PAGE
TITLE PAGE
DECLARATION DEDICATION
ACKNOWLEDGEMENT v ABSTRACT vi ABSTRAK vii TABLE OF CONTENTS viii LIST OF FIGURES xi LIST OF TABLES xii
LIST OF ABBREVIATIONS xiii LIST OF APPENDICES xiv
INTRODUCTION 1 1.1 Background 1 1.2 Problem Statement 3 1.3 Objective 3 1.4 Scope of Project 4 1.5 Thesis Outline 4
2 LITERATURE REVIEW 6 2.1 Introduction 6
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2.2 Swiftiets 6
2.3 Swifflet Attraction •8
2.3.1 Puller 9
2.3.2 External 9
2.4 Sound 10
2.5 Sound Characteristic 11
2.5.1 Pitch 11
2.5.2 Quality 12
2.5.3 Loudness 12
2.6 Sound Analysis 13
2.7 Fast Fourier Transform (FFT) Algorithm 14
3 RESEARCH METHODOLOGY 16
3.1 Introduction 16
3.1.1 Sample of Sound 17
3.1.2 Pre-processing 18
3.1.3 Analysis 18
3.1.4 Identify the sound characteristics 19
3.2 Sound Development 19
3.3 Software Development 22
4 RESULT AND DISCUSSION 23
4.1 Introduction 23
4.2 Swiftiets Sound 24
4.3 Signal of Swiflets Sound 24
4.4 Fast Fourier Transform (FFT) on swiftlets sound 26
4.5 The Original Sound Profile 29
4.5.1 Result for original sound in 60 seconds 29
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4.5.2 Result for original sound in 120 seconds 31
4.6 The Noise Sound Profile 34
4.6.1 Result for noise sound in 60 seconds 34
4.6.2 Result for noise sound in 120 seconds 36
4.7 The Sample Sounds in 60 seconds 39
4.8 The Sample Sounds in 120 seconds 41
4.9 Sound Characteristic for Swifflets Attraction 43
4.10 Problem Encountered 44
4.11 Summary 44
5 CONCLUSION AND FUTURE WORKS 45
5.1 Conclusion 45
5.2 Future Recommendation 46
REFERENCES 47
x
APPENDIES 49
LIST OF FIGURES
FIGURE NO. TITLE PAGE
2.1 Swiftiets 7 2.2 Swiftiets build nest from threads of their saliva 7 2.3 Puller locations at the swiflets's house 9 2.4 External locations in swiflets's house io 2.5 Frequency and wavelength of everyday sound 11 3.1 Block diagram for the flow of the project 17 3.2 Waveform presented the frequency and amplitude 18 3.3 Mp3 to Way converter 19 3.4 Block diagram for detail about sound development 20 3.5 Audio Cutter 21 3.6 Cut a sample of sound in the middle duration 2 minutes
(120 seconds) 21 3.7 Block diagram for detail about software development 22 4.1 Signal of swiftiet sound for 60 seconds 24 4.2 Signal of swifflet sound for 120 seconds 25 4.3 (a) Fast Fourier Transform (FFT) wave 26 4.4 (b) Left Hand Side (LHS) FFT wave 27 4.4 (c) Right Hand Side (RHS) FFT wave 27
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LIST OF TABLE
TABLE NO. TITLE
PAGE
4.1 Magnitude of original sound for 60 seconds 29
4.2 Frequency at RHS of original sound for 60 seconds 30
4.3 Frequency at LHS of original sound for 60 seconds 30
4.4 Magnitude of original sound for 120 seconds 31
4.5 Frequency at RHS of original sound for 120 seconds 32
4.6 Frequency at LHS of original sound for 120 seconds 32
4.7 Magnitude of noise sound for 60 seconds 34
4.8 Frequency at RHS of noise sound for 60 seconds 35
4.9 Frequency at LHS of noise sound for 60 seconds 35
4.10 Magnitude of noise sound for 120 seconds 36
4.11 Frequency at RHS of noise sound for 120 seconds 37
4.12 Frequency at LHS of noise sound for 120 seconds 37
4.13 Magnitude for 60 seconds 39
4.14 Frequency for 60 seconds 40
4.15 Magnitude for 120 seconds 41
4.16 Frequency for 120 seconds 42
xli
LIST OF ABBREVIATIONS
FFT - Fast Fourier Transform
RHS - Right Hand Side
LHS - Left Haid Side
xl"
LIST OF APPENDICES
APPENDIX TITLE PAGE
A Source Code 49
B Sample 1 50
C Sample 2 54
D Sample 3 58
E Sample 4 62
F Sample 5 66
G Sample 6 70
H Sample 7 74
I Sample 8 78
J Sample 9 82
K Sample 10 86
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CHAPTER 1
INTRODUCTION
1.1 Background
In this bustle development and modem century, healthy care is very important to
human for continue their life. To obtain good healthy we must remember prevent
disease better than treat. Because of that, we might need to choose health nutrition can
care our health such as bird's nest from swiftlets. The nests of some species are built
entirely from threads of their saliva, and are collected for the famous Chinese
delicacy bird's nest soup [1].
Minister of Agriculture and Agro Industrial, Datuk Seri Noh Omar said the nests
of swiftlets can give income that is luxurious for selling. This is because the demand
that is high in the whole world such as China, Japan, America and Europe but only
20%-30% fill up global demand and the profit will be getting 80%-90% from capital
production [2].
I
2
This is because Chinese medical study in Beijing find out swifflets's nest make
skin whiting agent and also good for eye's health. For asthma sufferer, it also became
best agent restore respiratory system and strengthens lungs.
Result of experiment and present research that bird's nest benefiting all age level
such as collagen nutrient which include in every swiftiets's nest can launch blood vessel
increase appetite and improve alimentary canal, swifflets's nest can reduce sputum and
heal cough, nutrition that is good for lungs and strengthen respiratory tract, swiftiets's
nest intake when pregnancy can lessen sense of pain in bottom strengthen baby lungs
that being included, accelerate healing process after giving birth, for woman
systematically nutrition can enhance metabolism force, improve skin and delaying
ageing process, for old people, systematically nutrition can strengthen vein and bone
also increase body resistance to illness, for children the bird's nest can magnify nutrition
absorbency that there is at every food and strengthen lungs and lastly elected as food
that is very good to smokers apart from being able to reduce effect that mooted from
from nicotine and prevent cancer attack [3].
The nests can give high potential and also benefiting for health although the
value reaches thousands of ringgit. Within more this a decade, entrepreneurs explored
various methods and new technology to increase production. There are a few factors to
make swiftiets attract such as aroma, light, temperature, humidity and sound. Report
from Department of Veterinary Services in Malaysia the swiftiets character is sensitive
toward sound. Previously, sound that produced at swiftiets husbandry premise actually
is produced from recording audio sound bird voice [4].
Therefore, the research and development about sound characteristic for swiftiets
attraction needed to develop swiftléts industry. This is use for industry to attract
swiftlets enter and build their nests in man-made house. The income can give benefits
for good economic and healthy.
3
1.2 Problem Statement
Nowadays, bird house for swiftiets farming usually developed and equipped
with recorded sound of chirping and mating from cave (natural habitat) to attract
swiftiets to enter and build nest. These sound just taken using trial and error method
without analysis (frequency, amplitude, wavelength, or other element) the elements of
sound involve in signal to attract the swiftiets. This method is sometimes successful to
attract the swiftiets, but certainly these sounds contains noisy and disturb by another
sound. There are no details researches about type of sound or characteristic of sound
that make the swiftiets attract.
1.3 Objective
The proposed analyze sound for swiftiets attraction by conducted some basic
objectives of research step. The following objectives are:
i. To analyze the sound for swiftlets attraction at location can attract the swiftiets
enter in swiftlets house.
ii. To find the elements of sound in the sound have been analyzed.
iii. To identify the sound of characteristic for swiftlets attraction.
4
1.4 Scope of Project
In order to achieve the research objectives, the following scopes will be
covered:
i. In this project, there are tens samples of sound have placed at external location
in swiftiets's house to be analyzed.
ii. Type of sound is one of the most factors in this project. So, I have decided to
choose analyzed the original sound and noise sound in aspect:
a) Frequency
b) Magnitude
1.5 Thesis Outline
This thesis is organized as below:
Chapter 1 will describes the introduction of this system, the purpose of this project,
problem statement, the work scope and brief explanation of this project.
In Chapter 2, the reviews about the information find on all the material or data used
include the software in the development of this project will be shown.
Chapter 3 will explain about all the methods use in development of this system and
also step by step on develop the module for training p pose and lastly described about
the execution part.
Chapter 4 will show all the results followed by the explanation and discussion about
the results from the beginning step until the end of development module.
Last chapter of Chapter 5 will have a summary to describe the overall part of this
project and come up with some recommendations and improvement.
CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
This chapter discusses on topics about swiftiets, sound, swiftiets attraction,
sound characteristic, and sound analysis. Furthermore, discussion on sound
classification FFT (Fast Fourier Transform) Algorithm and FFT application are
presented.
2.2 Swiftiets
Swiftiets are birds contained within the four genera Aerodramus, Hydrochous,
Schoutedenapus and Collocaija. They form the Collocaliini tribe within the swift family
7
Apodidae. This group contains around thirty species which is mostly confined to
southern Asia, south Pacific islands, and northeastern AiistrnIi All
the tropical and subtropical regions. They are in many respects typical members of the
Apodidae, having narrow wings for fast flight, with a wide gap and small reduced beak
surrounded by bristles for catching insects in flight [1].
"
Figure 2.1 Swiftlets
A small-sized swift (Family Apodidae) have 24 species worldwide. The main
producers of edible nest are White-nest Swiftiets (Aerodramusfuciphagus) and Black-nest Swiftlets (A. maximus). Two unique characters are salivary gland to build nest and
Echolocation [16].
Figure 2.2 Swiftlets build nest from threads of their saliva
8
The distinguishes are many but not all species from other swifts and indeed
almost all other bird is their ability to use a simple but effective form of echolocation to
navigate in total darkness through the chasms and shafts of the caves where they roost
at night and breed. The nests of some species are built entirely from threads of their
saliva, and are collected for the famous Chinese delicacy bird's nest soup [1].
2.3 Swiftlets Attraction
There are environmental factors such as temperature, light intensity, humidity
and sound is the key of successful place for swiftlets [8]. Sound is the main attraction
for swifflets for place in their house. The most interesting feature of swiftiets is that
many species utilize a sonar-like system [9]. The swiftiets's voice proven very effective
attracts swiftlets to be nested in bird house for swiftlets fanning [10]. This is shown that
swiftlets very sensitive on sound.
The previous research state that swiftlets hearing responses to the frequency I -
16 kHz [8] and which most energy on 2 - 5 kHz [12]. This frequency falls into normal
hearing. This statement is shown that in general, the animals generate sounds to
communicate with members of the same species [11]. hi year 1990, technique for
swiftlets attraction by using recording began to be expended but recording quality that
is adverse. Through technology development, swiftiets recording voice that produced
with quality, clear and similar authentic swiftiets voice. This swiftlets's recording voice
usable to increase swiftiets population to build nest. There are two locations to attract
the swjftlets entered the swiftlets farming house which are puller and external [10].
2.3.1 Puller
The locations at puller swiflets's house is on the roof house. Mostly, this
location will fit the swifilets voice when they gather.
e1- 1.
Figure 2.3 Puller locations at the swiflets's house
2.3.1 External
The location at external swiflets's house is on the outer house. Mostly, this
location will fit the adult swiftiets voice.
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Figure 2.4 External locations in swiflets's house
2.4 Sound
Sound is a mechanical wave that is an oscillation of pressure transmitted through
a solid, liquid, or gas, composed of frequencies within the range of hearing and of
a level sufficiently strong to be heard, or the sensation stimulated in organs of hearing
by such vibrations. Sound is a sequence of waves of pressure that propagates through
compressible media such as air or water. When sound is moving through a medium that
does not have constant physical properties i it may be refracted (either dispersed- or
focused). The perception of sound in any organism is limited to a certain range of
frequencies. For humans, hearing is normally limited to frequencies between about
20 Hz and 20,000 Hz, although these limits are not definite. The upper limit generally
decreases with age [6].
Sound is produced by the vibration of sound pressure waves in the air. Sound
pressure levels are used to measure the intensity of sound and are described in terms of
decibels. Sound is composed of various frequencies, but the human ear does not
I
respond to all frequencies. Frequencies to which the human ear does not respond must
be filtered out when measuring highway noise levels [7]. Sound is the important thing
for this project to find the characteristic of sound can attract the swiftiets and to know
that the frequency of swiftiets most attract can be heard by human or not.
2.5 Sound Characteristics
Sound can be heard from different quality of sounds, i.e. loud or soft, high pitch
or low pitch, audible or inaudible etc [7]. A sound can be characterized by the following
three quantities are pitch, quality and loudness.
2.5.1 Pitch
Pitch is the frequency of a sound as perceived by human ear. A high frequency
gives rise to a high pitch note and a low frequency produces a low pitch note. Figure 2.5
shows the frequencies of same common sounds.
1•1• I. iuIu1iIIIi)Iri1rh1ir. _______
ji10000 100000
Li11LiLU1U HIM UtLi1U Jill hLitUili
Figure 2.5 Frequency and wavelength of everyday sound
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2.5.2 Quality
A pure tone is the sound of only one frequency, such as that given by a tuning
fork or electronic signal generator. The fundamental note has the greatest amplitude and
is heard predominantly because it has a larger intensity. The other frequencies such as
2fo, 3fo, 4fo, etc. are called overtones or harmonics and they determine the quality of
the sound.
2.5.3 Loudness
Loudness is a physiological sensation. It depends mainly on sound pressure but
also on the spectrum of the harmonics and the physical duration [13]. Sound waves are
often simplified to a description in terms of sinusoidal plane waves, which are
characterized by these generic properties [6]:
i. Frequency
ii. Magnitude
iii. Amplitude
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2.6 Sound Analysis
There are many methods for analysis sound characteristic. For example sound
frequency characteristic based on Electroencephalography (EEG) signals. The study
includes feature extraction of the EEG signals with respect to different sound
frequencies, covering low frequency (40 Hz), mid-range frequency (5000 Hz), and high
frequency (15000 Hz) [14]. So, this project can use this technique by extraction of
sound signal get from sample to different sound frequency such as low frequency, mid-
range frequency and high frequency and combination of frequency called as full range
frequency.
In this journal, EEG signal characterization is done using Fast • Fourier
Transform (FFT), moving average filters, and simple artifact filtering with reference
EEG data per individual. Based on the characteristics of the EEG signal, the sound
frequency can be categorized and identified using the proposed method [14].
Otherwise, a method for identifying cutting sound characteristics for machine
tool industry based on a robust time-variant sound recognition system. The sound signal
is compressed using linear prediction analysis method. The procedure taken here is
based on the attraction of time-variant spectral features (example: raw data of sound)
and characterization of each sample by obeying the autocorrelation coefficients and
reflection coefficients of the sampled data. The proposed technique is shown to be very
effective, accurate, and powerful in performing sound data identification [15].
For this project, analysis for the sound is by taking a few sample of sound to
form a raw data of sound from different locations. Then, the data will be compared
based on the similarity elements in different location for characterizations which are
involved attracting the swiftiets.
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2.7 Fast Fourier Transform (FFT) Algorithm
Fourier analysis is useful for data analysis, as it breaks down a signal into
constituent sinusoids of different frequencies. It is particularly used in area such as
signal processing [17].
Therefore, short time Fourier Transform (STFT) have been deployed using a
variety of "windows" with different relative advantages to address principally
difficulties in analyzing short term transient sound behavior [18]. Two things that are
different about the FFT implementation in Matlab than the presentation the FFT uses
complex numbers and the FFT computes positive and negative frequencies [19].
There is better way to compute the Fourier transform of discrete data called the
FFT. The FFT was a truly revolutionary algorithm that made Fourier analysis
mainstream and made processing of digital signals commonplace. The power of the
FFT is that it allows computing the Fourier coefficients faster. The FFT has become
such a commonplace algorithm that it is built into Matlab. The coefficient FFT is quite
complex [20].
Use of complex numbers introduces some mathematical simplicity in Fourier
transform algorithms and provides a convenient representatiop. Real numbers are often
represented on the real number line and complex numbers are often visualized on the
two dimensional complex plane. In the complex plane it is clear to see that the absolute
value is simply the distance of the cothplex number from the origin.