Abstract - Hong Kong Polytechnic Universitymwmak/fyp/3D-sound/report.pdf · Abstract In this...

Department of Electronic and Information Engineering Ngan Cheuk Yin

The Hong Kong Polytechnic University, Hung Hom of 74

April, 2002

Abstract

In this project, I use the Head Related Transfer Functions (HRTFs)

to illustrate how a monaural sound synthesizes some particular sounds in

3-D space. It comprises a study of HRTF and an explanation of creating a

3-D environment.

I employed some HRTF measurements of MIT Laboratory and my

Matlab codes to generate “spatialized” sounds. To enhance my design, I

produced a simple graphical interface for users to activate the operation

of HRTFs. In GUI window, one simply clicks the mouse and some

processes will be performed in the background. Thus, HRTF-sounds

come in different directions.



April, 2002

Acknowledgements

I thank those for encouraging me to begin, continue, finish, and

cherish my time as a graduate student here in the Hong Kong Polytechnic

University. I offer my deepest thanks:

To my supervisor, Dr. Mak Man Wai of the Electronic and

Information Engineering Department, thanks for his guidance, patience

and wisdom over the past years. Without his support, none of this could

be possible.

To all of my teachers, past and present, in and out of school, for

caring for me and training me.

Finally, thanks to my parents for their incessant love, support,

affection, and encouragement. Thank you very much!



April, 2002

Content

Abstract...........................................................................................................................1

Acknowledgements........................................................................................................2

Content............................................................................................................................3

List of Tables ..................................................................................................................5

List of Figures.................................................................................................................6

Chapter 1: Introduction..................................................................................................8

1.1 Motivation..............................................................................................................8

1.2 Objective of the work............................................................................................9

1.3 Scope of thesis .....................................................................................................9

1.4 Details of relevant theory ...................................................................................10

1.4.1 HRTF's - Head Related Transfer Functions................................................10

1.4.2 Overview of the human ear .........................................................................13

Chapter 2 Project Implementation ..............................................................................15

2.1 Review of MIT HRTF’s measurements ..............................................................15

2.1.1 Measurements Data .....................................................................................16

2.2 Review of past work ...........................................................................................18

2.3 Introduction of proposed work..........................................................................19

2.4 System Architecture and Requirements...........................................................20

2.4.1 Hardware.......................................................................................................20

2.4.2 Software ........................................................................................................20

Chapter 3 Methodology..............................................................................................21

3.1 Matlab Scripts in Details ....................................................................................21



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3.1.1 Interface codes.............................................................................................23

3.1.1.1 hrtf.m ..................................................................................................... 23 3.1.1.2 verti_sur.m ............................................................................................ 26 3.1.1.3 hori_sur.m ............................................................................................. 28

3.1.2 HRTF codes for verti_final.m and hori_final.m..........................................30

3.2 Input Parameters ................................................................................................37

3.3 Output Parameters..............................................................................................37

Chapter 4 HRTF Results ............................................................................................38

4.1 Comparison HRTF-sound with common stereo sound ...................................39

4.2 Wave Statistics from different condition ..........................................................42

Chapter 5 User Manual of 3D Simulation ...................................................................48

5.1 Setting the input and output file name: ............................................................50

5.2 Setting Parameters of Horizontal Surround .....................................................51

5.3 Setting Parameters of Vertical Surround..........................................................53

5.4 Processing the parameter..................................................................................56

5.5 Close the window................................................................................................56

Chapter 6 Conclusion ..................................................................................................57

6.1 Problems with HRTF-based synthesis of spatial audio...................................57

6.2 Headphones ........................................................................................................58

6.3 Future Work.........................................................................................................58

Appendices...................................................................................................................60

Homepage of my project ..........................................................................................60

Pseudo-code of Matlab scripts................................................................................61

References....................................................................................................................74



April, 2002

List of Tables Table 2.1 Number of measurements and azimuth increment at each elevation…….17

Table 3.1 The Matlab Scripts in my project and their objectives………….….…..…...21

Table 3.2 Sub-functions in hrtf.m of my project and their objectives……….…….….23

Table 3.3 Sub-functions in verti_sur.m of my project and their objectives……….…26

Table 3.4 Sub-functions in hori_sur.m of my project and their objectives…………..27



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List of Figures Figure 1.1 distribution of sound source of measurements …………………….......10 Figure 3.1 hrtf.fig in GUIDE……………………………………………………..……..22 Figure 3.2 verti_sur.fig in GUIDE………………………………………………….…..25 Figure 3.3 hori_sur.fig in GUIDE……………………………...……………….….......27 Figure 3.4 flow Chart of hori_final.m and verti_final.m……………….……..….…..29 Figure 3.5 pseudo-codes of verti_final.m and hori_final.m………………..….…....31 Figure 3.6 pseudo-codes of cir_mon.m and cirsft.m………….………….…………32 Figure 3.7 illustration of sound sample, and prediction error for sound

where the prediction error is large at the end of the section….……....33 Figure 3.8 block convolution using the overlap-save method………….…….…….34 Figure 3.8 (a) input signal x(n) divided into overlapping sections,overlap is Nh-1=2...34 Figure 3.8 (b) impulse response h(n) …..…………………………………... ………..….34 Figure 3.8 (c) output y(n) using direct convolution …..…………………...………........34 Figure 3.8 (d) output y1(n) for block circular convolution of x1(n) and h(n) ….…….....34 Figure 3.8 (e) output y2(n), (f) output y3(n) ………………………..……….…….…..….34 Figure 3.8 (g) output y4(n) ……………………..……………………….….…...……..…..34 Figure 3.8 (h) sequential concatenation of block outputs after discarding the first

two samples of each block, which is equivalent to the direct convolution result "|" represents concatenation………………...…..…..34

Figure 3.9 overlap-save methods in this program…………………………..……….35 Figure 4.1 graph of GloryBe.wav and its spectrogram………………….……………37 Figure 4.2 graph of GloryBe.wav after HRTF processing and its spectrogram…...38 Figure 4.3 simulation of stereo sound of GloryBe.wav by one application and

its spectrogram……….…………………………………………....…….....39

Figure 4.4 3D surface of the GloryBe.wav in frequency expression……………….40 Figure 4.5 flow and graph of GloryBe.wav HRTF sound flowing from the

front to the back…………………………………………………….………..41 Figure 4.6 flow and graph of GloryBe.wav HRTF sound flowing a cycle………...41



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Figure 4.7 spectrogram of the wave in Figure 4.6 and left side is at elevation 0° and the right side is at elevation 50°…………………………………...42 Figure 4.8 flow and graph of GloryBe.wav HRTF sound flowing in the front

from -40° to 90°…………..……………...……………………………………43

Figure 4.9 flow and graph of GloryBe.wav HRTF sound flowing in the right from -40° to 90°…………………………………..…………………………...43

Figure 4.10 flow and graph of GloryBe.wav HRTF sound flowing in the back

-40° to 90°……………………………………………..….…………………...44

Figure 4.11 flow and graph of GloryBe.wav HRTF sound flowing in the left from -40° to 90°………..…………………………………………….…...…..44

Figure 4.12 flow and graph of GloryBe.wav HRTF sound flowing from the

front to the back through the above of head……………………….….…...45

Figure 4.13 flow and graph of GloryBe.wav HRTF sound flowing in from the right to the left through the above of head………………..……….…..45

Figure 5.1 Matlab 6.0 first pages………………….………………………………..…...47 Figure 5.2 initial “HRTF based surround sound” window……………………………..47 Figure 5.3 pop-up window for choosing the output file name………...……………...49 Figure 5.4 “HRTF based surround sound” after choosing input and output file name………………………………………………..……….….…50 Figure 5.5 initial window of “ Setting Horizontal Surround Sound Parameters”……………………………………………...…….……….…….50 Figure 5.6 window of “ Setting Horizontal Surround Sound Parameters” after setting parameter…………………………………………….………...51 Figure 5.7 initial window of “Setting Vertical Surround Sound Parameters”……….52 Figure 5.8 window of “Setting Vertical Surround Sound Parameters” after pressing “Route of Wave”. A picture loaded in the blank box when choosing “Spcify azimuth angle”……………………….………….………..53 Figure 5.9 window of “Setting Vertical Surround Sound Parameters” after pressing “Route of Wave”. A picture loaded in the blank box when choosing “Semi_Circle azimuth angle”……………………….……….…...54 Figure 5.10 Message box for referencing the completing of processing…………..54 Figure 5.11 Message box asking user for choosing the close operation…………...54



April, 2002

Chapter 1: Introduction

1.1 Motivation

Directional hearing refers to the sensory attribute that enables humans to

determine the location of a sound source in both azimuth (left/right) and elevation

(up/down) position. Sounds give the sensation of direction called “spatialized sounds”.

[1] The ability of humans to perceive the spatial location of sound in space is truly a

remarkable skill. Not only the auditory systems localize sounds with extraordinary

accuracy, but spatial hearing mechanisms are also exceptionally robust under the

most extreme of listening conditions. To get better control of spatial sound in various

applications, researchers from all fields have sought to understand how the human

auditory system accomplishes spatial hearing. Recently, advances in computational

power and acoustic measurement techniques have made spatial hearing possible to

empirically measure, analyze, and synthesize the spectral cues. These spectral cues

are called Head Related Transfer Functions(HRTF’s) sound.[2] Loosely speaking,

HRTF’s are filters, which describe the acoustic filtering the head, torso, and external

ear(pinna) performed on a sound, and use to simulate the illusion of spatial sound

over headphones. HRTF data sets presumably contain all of the sonic cues affecting

the perception of spatial location for a specific individual.



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1.2 Objective of the work

I have completed a program which aims to transfer a monaural sound to a

stereo one. The headphone listener can perceive processed sound at any specified

locations in space such as front, back, right or left. I use head-related transfer

functions (HRTFs) to impart sound localization cues. The apparent direction of

incidence of sound (the signal) can be manipulated with it.

HRTF’s measurements I used are produced by Bill Gardner and Keith Martin at

the MIT Media Lab [4] which uses a KEMAR (Knowles Electronics Manikin for

Auditory Research) Dummy-Head Microphone. [5] This data was available for public

use. The tools and database for HRTF processing was described in detail below.

1.3 Scope of thesis

This thesis is structured as follows. In the rest of Chapter 1 briefs relevant

theories such as Head-Related Transfer Function (HRTF), interaural transfer function

(ITF) and the interaural time difference (ITD). [6] I give an overview of human ear.

Chapter 2 investigates the project implementation. First, I take a review of MIT

HRTF’s measurements. It explains how the MIT Laboratory gets HRTF measurements.

Then, I tell what I did last year. I will also state the system architecture and some

requirements of my program. Chapter 3 is about methodology. I explain the

architecture of Matlab scripts in greater details. For example, I draw the program flow

of HRTF.m, verti_sur.m, hori_sur.m, verti_final.m and hori_final.m.



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In chapter 4, I paste some processed wave statistics and spectrograms of

GloryBe.wav and present out some characteristics of HRTF-based sound. Finally,

Chapter 5 provided some conclusions and future directions.

1.4 Details of relevant theory

1.4.1 HRTF's - Head Related Transfer Functions

The transformation of a sound wave from a source to the ear is normally

described by a transfer function called the head-related transfer function (HRTF). The

HRTF is a frequency-function of a signal and the location of the source with respect to

head. The source’s azimuth angle and elevation angle location use to specify the

location of source. A complete set of HRTF measurements consists of many filters

that describe a spherical map of the possible sound sources. It contains information

about frequency dependent sound delays and intensity differences between ears.

When a signal sends through

Figure 1.1 Distribution of sound source in the measurements



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HRTF filter and then plays through headphones, the listener receives the impression

of the sound source.

In above pictures, each point represents a sound source. The distance of the

source is a constant relative to the center of the head. Sources change in the lateral

position around the azimuth or the elevation of the source. The differences in delay

and intensity between ears are greatest in the azimuthally position and less so for

elevation. These differences are also frequency dependent.

Let me consider a sound source located at azimuth angle θ with respect to the

head. Let S (ω) be the Fourier transform of the source signal, HX(ω, θ) and HY (ω, θ)

be the Fourier transform of the signals of left-ear and right-ear respectively.

X(ω, θ) = HX(ω, θ)S(ω)

Y (ω, θ) = HY (ω, θ)S(ω)

Next, we define,

F(ω, θ) = HY (ω, θ) HX(ω, θ)

F (ω, θ) is known as the interaural transfer function (ITF). [6] The interaural

transfer function captures the important binaural cues. The interaural time difference

(ITD) [6] is captured in the phase information of the ITF. More specifically, the

derivative of arg(F(ω, θ)) with respect to ω give the ITD. Note that introduction of

frequency dependent HRTF results in dependence of the interaural time (phase)

difference on frequency. The ITF could be estimated by taking the ratio of Fourier

transforms of the signals receive at the left-ear and the right-ear.

F(ω, θ) = Y (ω, θ) X(ω, θ)

It is important to note that F (ω, θ) is independent of the source spectrum and

thus could be used to find the location of any wideband source. This observation could



April, 2002

be utilized for finding a simple way of solving the sound localization problem using a

priori information. Suppose the actual interaural transfer function of the head, F (ω, θ),

is known a priori. This information is obtained from a training process. Later, in order

to estimate the direction of an unknown source signal, one can estimate the interaural

transfer function of the head from the received signals using F(ω, θ) = Y (ω, θ) X(ω, θ)

and compare it with the known F(ω, θ). The value of θ for the estimated interaural

transfer function is lost. The actual interaural transfer function gives the direction of

the source.

HRTFs are created from ITD, IID and pinna measurements associate with a

certain azimuth and possibly distance. HRTF parameters can be measured using

either real human heads or dummy heads. Tiny microphones are inserted into the ear

canals, and a recording is made of a sound source from many different azimuths and

elevations. Each particular measurement represents one sound source direction.

HRTFs provide insight into localization cues. For example, inspection of HRTFs for

sounds coming directly from the right at different elevations would show the effects of

pinna filtering. The notches in the filtered frequency response would change in

number and frequency position with different elevations as direct and indirect sounds

combine in the ear. This particular data would help reveal how we detect elevation.

In addition, HRTF processing uses to trick the ear. For example, a sound from

a stationary speaker at an arbitrary elevation can be processed by this series of

HRTFs. As its frequency response gradually changed, the ear/brain would perceive

changing elevation from the stationary source. Similarly, complex surround sound

fields can be synthesized from stereo speakers, but the ear isn't always entirely fooled.



April, 2002

The realism of the created sound field will suffer if the listener moves from the "sweet

spot" between the speakers (headphones solve this problem) because the delicate

balance of cues will be upset. Moreover, the folds of each listener's pinna are different;

generic HRTFs are exactly not matching our own psychoacoustic expectations. In PC

sound cards, using cross-talk cancellation techniques to improve perceived channel

separation cleans up the 3D sound image in two channels, but headphones, with their

superior real channel separation deliver a better two-channel experience. This type of

sound field rendering in two channels is called binaural rendering.

The human ear's purpose in the area of hearing is to convert sound waves into

nerve impulses. These impulses are then perceived and interpreted by the brain as

sound. The human ear can perceive sounds in the range of 20 to 20,000 Hz. This

section is broken down into a basic overview of the ear; the ear receives a section of

how sound, a section on how the ears communicate with the brain, and finally, a

section of human factors. Understanding how the ear worked is the key to

successfully implementing 3D sound in VR systems.

1.4.2 Overview of the human ear

The human ear is made of three distinct areas: the outer ear, the middle ear,

and the inner ear. The outer ear channels sound waves through the ear canal to the

eardrum.



April, 2002

The outer ear (pinna) is considered an auditory cue in HRTF generation. The

eardrum is a thin membrane stretched across the inner end of the canal. HRTF

generation uses small microphones embedded in a real ear canal to help simulate the

real acoustic environment. Air pressure changes in the ear canal cause the thin

membrane to vibrate. These vibrations are transmitted to three small bones called

"ossicles" which are located in the air-filled middle ear and conducted the vibrations

across the middle ear to another thin membrane called the oval window. All of these

vibrations are different when a small microphone is embedded in the ear canal, thus it

is impossible to accurately simulate the acoustic environment of the human ear using

this method (HRTF measurements). The use of a small microphone in the ear canal

approximated the real thing. It is because frequency response, position, reflection and

refraction of sounds waves are different. The problem is trying to make measurements

without affecting the measurements. The oval window separates the middle ear from

the fluid-filled inner ear. The effect that the fluid filled inner ear has on sound

transmission is not modeled at all in HRTF generation, in fact, HRTF generation

basically attempts to measure affects of external structures and immediate results

inside the ear canal. Everything happen from middle ear on back is not modeled at all.

The "cochlea" in the inner ear is the most important component of hearing. It

contains the organ of "Corti". The Corti sit in an extremely sensitive membrane called

the "basilar membrane". Whenever the basilar membrane vibrates, small sensory hair

cells inside the Corti are bent, which stimulates the sending of nerve impulses to the

brain.



April, 2002

Chapter 2 Project Implementation 2.1 Review of MIT HRTF’s measurements

For this project, I used HRTF measurements compiled by researchers working

in sound media lab in MIT. There are three types of data sets that they have made

publicly available. The "compact data set" is a set of impulse responses, which have

been preprocessed to compensate for recording equipment response and other

factors, and is ready to be used directly. The ‘full data set’ is recorded when they are

generating the data. We prefer to use the compact data set for various reasons. The

advantage of this is that data was equalized to compensate for the non-uniform

response of the Optimum Pro 7 speaker. The full data set have 512 taps for the FIR

filter instead of 128 taps in the compact data set. Finally, the diffused field set data is

compensating for the recorded equipment’s response that allows us to emphasize the

difference.

The MIT researchers use a manikin, named KEMAR, in their experiment. They

set up microphones in its ear canal and played sounds from different locations using

speaker about 1.4 meters apart from the head. Responses from total of 710 different

locations are recorded using sampling frequency of 44.1 KHz. A non-

echoic room uses for the purpose.

Utilizing the symmetry of the head, the KEMAR is set up with two

different pinnae. The left pinna in KEMAR is a normal pinna, while the

right pinna is a slightly larger one. The microphones in the KEMAR’s



April, 2002

ears also pick up the ear canal resonance of the manikin’s ears during recording

sound. When these HRTFs are used to generate sound, the listener will hear the

KEMAR ear canal resonance in addition to his own ear canal resonance. Besides that,

as mentioned earlier, the full data set contains the recording system’s response too. A

possible way to eliminate the measurement system’s response, as well as effect of ear

canal resonance is to normalize the measurements with respect to an average across

all directions (called diffuse-field equalization). Since neither the measurement system

response nor the ear canal response change as a function of sound direction, they will

be factored out of the data. To find the diffuse field data, the magnitude-squared

responses of all responses are averaged, which results in power average across all

directions. My project is using the diffuse field data. It uses the pre-computed value of

inverse diffuse field to process the sound before playing. In general, the sounds

synthesized using diffuse-field data can be localized better. The purpose is to provide

the option there is to allow the users to evaluate its effect themselves.

2.1.1 Measurements Data

The spherical space around the KEMAR is sampled at elevations from -40

degrees (40 degrees below the horizontal plane) to +90 degrees (directly overhead).

At each elevation, a full 360 degrees of azimuth is sampled in equal sized increments.

The increment sizes are chosen to maintain approximately 5-degree great-circle

increments. The table below shows the number of samples and azimuth increment at

each elevation (all angles in degrees). A total of 710 locations are sampled.



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elevation angle no. of measurement azimuth increment

-40 56 6.43

-30 60 6

-20 72 5

-10 72 5

0 72 5

10 72 5

20 72 5

30 60 6

40 56 6.43

50 45 8

60 36 10

70 24 15

80 12 30

90 1 x

Table 2.1: Number of measurements and azimuth increment at each elevation

Each HRTF measurement yields impulse response at a 44.1 kHz sampling rate.

Most of this data is irrelevant. The impulse responses are stored as 16-bit signed

integers, with the most significant byte stored in the low address (i.e. Motorola 68000

format). The HRTF data is stored in directories by elevation. Each directory name

has the format ``elevEE'', where EE is the elevation angle. Within each directory each

filename has the format ``HEEeAAAa.dat'' where EE is the elevation angle of the

source in degrees, from -40 to 90, and AAA is the azimuth of the source in degrees,

from 0 to 355. Elevation and azimuth angles indicate the location of the source relative

to the KEMAR, such that elevation 0 azimuth 0 was directly in front of the KEMAR,

elevation 90 is directly above the KEMAR, elevation 0 azimuth 90 is directly to the

right of the KEMAR, etc. For example, the file ``H-20e270a.dat'' is the right ear

response, with the source 20 degrees below the horizontal plane and 90 degrees to

the left of the head. Note that three digits are always given for azimuth so that the



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files appear in sorted order in each directory. To select a pair of HRTF responses, I

recommend using symmetrical responses obtained from one of the KEMAR ears.

2.2 Review of past work

I had completed stage one and wrote custom scripts in last year. These scripts

directly convolved an input file (in *.wav format) with a selected head-related transfer

function (HRTF) to simulate an incidence of source at a particular azimuth and

elevation. A stereo output sound is produced for binaural presentation to the subject.

HRTF processing and signal mixing is implemented in one MATLAB [3] script

Stereo.m.

Stereo.m is invoked from the MATLAB command line by optionally providing

parameter values in the function call. If no parameters are provided in the function call,

the script set most parameters to default values (e.g., the default for azimuth and

elevation angles was 0 degrees for both). Stereo.m opens a file requester to ask user

to specify the input wave file. Then all wave files contain in the same directory as the

file specified would then be processed and the results are saved in a subdirectory

named HRTF. If not specified in the function call, the first time a stereo input file is

encountered the user would be requested to select which side to process (the input

signal x (n) must be monophonic).



April, 2002

2.3 Introduction of proposed work

In this semester, I added more functions and a graphical user interface to the

program. GUI is enhanced the user-friendly of my project. User needs to set the input

directory, input wave file, output wave file and which surrounding surface space

(horizontal or vertical HRTF). If user is pressing horizontal or vertical button, another

pop-up window called the user to enter the range of azimuth and elevation value. To

close these pop-up windows, the parameters would call back the hrtf.m. Then users

press the “Process” button to call other Matlab script files either hori_final.m or

verti_final.m to process HRTF simulation. After trimming the ends, the sound is

created in the output file.

The way of playing sound data is using sound (vector, fs) function of MATLAB.

[3] I opted to use wavplay ( ), a freeware in Matlab, that is suitable for playing sounds

on PCs. An added advantage that I get from wavplay( ) is that it waited for the sound

port to be released if it’s already busy. The user would play the sound when press the

“Playback” in GUI window or play with other application tools by just clicking the file

name.



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2.4 System Architecture and Requirements

2.4.1 Hardware

Pentium, Pentium Pro, Pentium II, Pentium III, Pentium IV based personal

computer

64 MB RAM minimum, 128 MB RAM recommended

Microsoft Windows supported graphics accelerator card and sound card

Headphones, Microphone

2.4.2 Software

Microsoft Windows 95, Windows 98, Windows ME, Windows NT 4.0 (with SP5 or

SP6a), Windows 2000, Windows XP

Matlab 6



April, 2002

Chapter 3 Methodology

3.1 Matlab Scripts in Details

There are thirteen Matlab scripts in my project. Some are used in the interface

while the other in the HRTF-convolution. The following table states their names and

objectives:

Scripts Name Objectives

hrtf.m This script calls for the main GUI window

to retrieve data from a user and transfer

data to other sub-functions

verti_sur.m This script calls for the vertical HRTF

window when a user presses “Vertical

Surround” button in the main window. It

retrieves some data like the range of

azimuth or elevation angles, and returns

the data to hrtf.m.

hori_sur.m This script calls for the horizontal HRTF

window after a user presses “Horizontal

Surround” button in the main window. It

retrieves some data like the range of

azimuth or elevation angles, and returns

them to hrtf.m.

modaldlg.m This script calls for “closing confirm

window” after a user presses the “Close”

button in the main window.

verti_final.m This script is called by hrtf.m after a user

has pressed the “Process” button and

chosen the horizontal HRTF. It also calls

for the other scripts to activate HRTF-

processing.



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hori_final.m This script is called by hrtf.m after a user

has pressed the “Process” button and

chosen the horizontal HRTF. It also calls

the other scripts to activate HRTF-

processing.

readhrtf.m This script returns HRTF measurements to

two columns of 128 rows. The first column

is left channel and the second column is

right channel.

hrtfpath.m This script returns the pathname of HRTF

data file to readhrtf.m.

group_file.m This script uses to group a sound clip with

stereo channels, left and right.

par_ser.m This script divides the mono sound clip into

parts of clips.

half_circle.m This script is called by hori_final.m when

user chooses 180º surrounding.

cir_con.m This script uses to do the circulate

convolution.

cirsft.m This script is called by cir_con.m.

Table 3.1 The Matlab Scripts in my project and their objectives



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3.1.1 Interface codes

3.1.1.1 hrtf.m

The hrtf.m contains sub-functions that launch and control GUI and callbacks.

Each callback refers to relevant object stored in hrtf.fig. Users use it to implement

HRTF-synthesis after retrieving data and transferring data to other scripts for

processing. The pseudo-code of hrtf.m is attached in Appendix.

Figure 3.1 of hrtf.fig in GUIDE



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The followings are descriptions of sub-functions in hrtf.m:

Sub-function Name Link with which object in

hrtf.fig

Function

listbox1_Callback “Listed File” list box It uses a list box to display

the files in a directory.

When the user double clicks

on a list item, one of the

following happens: If the item is a file, the GUI

opens the file appropriately

for the file type.

If the item is a directory, the

GUI reads the contents of

that directory into the list

box.

If the item is a single dot (.),

the GUI updates the display

of the current directory.

If the item is two dots (..),

the GUI changes to the

directory up one level and

populates the list box with

the contents of that

directory.

load_listbox X This sub-function retrieves

the path of a directory and

set the handles structure

from the listbox1_Callback

to be input arguments.

selectedfile_Callback “Input File Name”

edit box

This function uses to display

the input file name

outfile_Callback “Output File Name”

edit box

This function uses to display

the output file name



April, 2002

savefile_name_Callback “Choose Output File

Name”

push button

This function uses to

prompt a dialog box for

user entering the output file

name

hori_button_Callback “Horizontal Surround”

push button

This function generates a

call to the hori_sur.m and

return parameters when

pressing the button.

verti_button_Callback “Vertical Surround“

push button

This function generates a

call to the verti_sur.m and

return parameters when

pressing the button.

initial_button_Callback “Reset” push button This function uses to

initialize all the state of

hori_button_Callback and

verti_button_Callback

processing_Callback “Process” push button This function generates a

call to process HRTF-

synthesis

playback_Callback “Play” push button This function plays the

HRTF- sound by calling

wavplay function

close_Callback “Close” push button This function calls the

modaldlg.m function

figure1_CloseRequestFcn X This function call the

close_Callback.m

Table 3.2 sub-functions in hrtf.m of my project and their objectives



April, 2002

3.1.1.2 verti_sur.m

It is another script that contains functions to launch and control the GUI and

callbacks. The pseudo code is in Appendix.

Figure 3.2 of verti_sur.fig in GUIDE

There are two special functions “uiwait“ & “uiresume”. They use to stop and

resume MATLAB program execution. In the dialog, user calls a uicontrol with a

callback (uiresume) that destroys the dialog box. The “uiwait” is a convenient way to

use the wait for command. You typically use it in conjunction with a dialog box. It

provides a way to block the execution of the M-file that created the dialog, until the

user responds to the dialog box. When one uses conjunction with a modal dialog, the

“uiwait” causes MATLAB program to wait before returning execution to the Close

button callback.



April, 2002

The followings are descriptions of sub-functions of verti_sur.m:

Sub-function Name Link with which object

in verti_sur.fig

Function

verti_azim_radio_Callback

“Specify azimuth

angle” radio button

This function calls another

functions mutual_exclude

which makes inactive to

verti_semi_radio_Callback

from group of two radio

buttons.

azim_angle_popup_Callback

“Specify azimuth

angle” popup menu

This function prompts a

list of azimuth angles when

users press the arrow.

verti_semi_radio_Callback

“Semi_Circle azimuth

angle” radio button

This function calls another

functions mutual_exclude

which makes inactive to

verti_azim_radio_Callback

from group of two radio

buttons.

sc_azim_angle_popup_Callback

“Semi_Circle azimuth

angle” popup menu

This function prompts a

list of azimuth angles when


verti_reset_button_Callback “Reset” press button This function reset all

handles objects in the

“verti_sur.fig”

mutual_exclude X This function ensures all

buttons in the group which

must be deselected when

one of them is selected and

in active



April, 2002

verti_close_button_Callback “Close” press button This function resumes

program execution, and

runs the script of delete

(fig).

load_picture X This function uses to

display the path of the

HRTF sound

Show_pic_Callback “UpdatePic”press

button

This function aims to call

load picture function.

Table 3.3 sub-functions in verti_sur.m of my project and their objectives

3.1.1.3 hori_sur.m

Figure 3.3 of hori_sur.fig in GUIDE



April, 2002

The followings are descriptions of sub-functions in hori_sur.m:

Sub-function Name Link with which object in

hori_sur.fig

Function

hori_end_azim_Callback “End Azimuth Degree”

popup menu

This function displays a list

of end azimuth angles when


hori_elevslider_Callback “hori_elevslider” slider This function uses a slider

to specify elevation angle

since these components

enable the selection of

continuous values within a

specified range.

hori_elev_Callback “Selected Elevation Degree“

edit box

This function displays the

selected elevation degree.

hori_close_button_Callback “Close” press button This function resumes

program execution of

figure1, then run the script

of delete(fig).

load_picture X This function uses to

display the path of the

HRTF sound

show_Pic_Callback “UpdatePic”press button This function aims to call

load picture function.

Table 3.4 sub-functions in hori_sur.m of my project and their objectives



April, 2002

3.1.2 HRTF codes for verti_final.m and hori_final.m

These two scripts aim to take a monophonic input signal x (n) from a wave file

and convolve it with the appropriate pair of HRTFs to make the resulting signal

(presented binaurally). It checks and receives parameters from hrtf.m. Then it lists the

measurements used in processing and gets them with the input signal.

Check parameters received from the interface windows

Check number of measurements in the chosen

directory

Start

Determine and set the processing angles

Read the sound into a double array

Ensure the sound frequency in 44.1kHz

J=1

Call the sub-function cir_con for circular convolution

J> number of mesurements

J=J+1

Write the output hrtf sound

End

No

Yes

Figure 3.4 Flow Chart of hori_final.m and verti_final.m



April, 2002

Pseudo-Code of verti_final.m %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction verti_final(verti_choice,verti_val,filename,outfile_name)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Check parameters (verti_choice & verti_val) and then,

Set (azim_choice, azimangle, verti_gp_index, choose_index)

Set azim_dir=sprintf('%s', azim_choice)

Set directory located of the MIT lab contributed data files

Set the wave files in the selected directory to the matrix (filelist)

Set num_file = Nunber of file in the selected directory

%%

LOOP FOR i= 1 to num_file by 1

Set len=length(filelist(i).name)

Set elevangle(i)=str2num(filelist(i).name(2:4))

END OF FOR LOOP

Read the wave file into [input,fs,nbits] using wavread

Set newlength=num_file*fix(length(input)/num_file)

Set input=input(1:newlength)

Set zero padding number(n_z)=128-1

Set n_c=(newlength+(n_z*num_file))/num_file

Set x1=par_ser(input',128,n_c,num_file)

[m,n]=size(x1)

LOOP FOR k=1 to m by 1

Call the subfunction hrtf = readhrtf( elevangle(k), azimangle,choose_index )

Set left_rep=hrtf(:,1)

Set right_rep=hrtf(:,2)

Set len_imp=length(left_rep)

%% Do block circular convolution

Set x2=x1(k,:)

Call the subfunction left_blk_con(k,:)=cir_con(n_c,x2,left_rep')

Call the subfunction right_blk_con(k,:)=cir_con(n_c,x2,right_rep')

Set left_blk_lap(k,:)=left_blk_con(k,n_z+1:n_c)

Set right_blk_lap(k,:)=right_blk_con(k,n_z+1:n_c)

END OF FOR LOOP

Call the subfunction group_file

Retrieve data from group_file

Create the output wave file

Pseudo-code of hori_final.m



April, 2002

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction hori_final(start_angle,end_angle,elevangle,filename,outfile_name)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Set elevangle=10*(round(elevangle/10))

Set choose_index=1

Set elev_dir=sprintf('%s%d','elev', elevangle)

Set t the MIT lab contributed data files of the selected directory to the matrix (filelist)

IF start_angle=0 & end_angle=360 ,then

Set num_file=Nunber of file in the selected directory

ELSEIF start_angle=0 & end_angle=180

Call Subfunction [num_file]= half_circle(elevangle,filelist);

ELSE

Error_Message='Wrong number of input arguments','Input Argument Error'

ENDIF start_angle=0 & end_angle=360


Set len=length(filelist(i).name)

Set azimangle(i)=str2num(filelist(i).name(len-7:len-5))

END OF FOR LOOP

Read the wave file into [input,fs,nbits] using wavread

Set newlength=num_file*fix(length(input)/num_file)

Set input=input(1:newlength)

Set zero padding number(n_z)=128-1

Set n_c=(newlength+(n_z*num_file))/num_file

Set x1=par_ser(input',128,n_c,num_file)

[m,n]=size(x1)

LOOP FOR k=1 to m by 1

Call the subfunction hrtf = readhrtf( elevangle, azimangle(k),choose_index )

Set left_rep=hrtf(:,1) and right_rep=hrtf(:,2)

Set len_imp=length(left_rep)

Set x2=x1(k,:)

Call the subfunction left_blk_con(k,:)=cir_con(n_c,x2,left_rep')

Call the subfunction right_blk_con(k,:)=cir_con(n_c,x2,right_rep')

Set left_blk_lap(k,:)=left_blk_con(k,n_z+1:n_c)

Set right_blk_lap(k,:)=right_blk_con(k,n_z+1:n_c)

END OF FOR LOOP

Call the subfunction group_file to retrieve data to create hrtf wave file

Figure 3.5 Pseudo-codes of verti_final.m and hori_final.m



April, 2002

In these two scripts, I call another script(cir_con.m) to do circular convolution.

The cir_con.m calls for cirsft.m to cut the matrix in a suitable length and size.

Figure 3.6 Pseudo-codes of cir_mon.m and cirsft.m

This convolution in cir_con.m is using overlap-save method, which prevents the

prediction error at the beginning of each section of clip. The processed data by direct

Pseudo-Code of cir_con.m

%%%%%%%%%%%%%%%%%%%%%

Subfunction y=cir_con(n_c,x_in,cir_in)

%%%%%%%%%%%%%%%%%%%%%

Set x_inn=[x_in(1:length(x_in)) zeros(1,n_c-length(x_in))]

Set imp_in=[cir_in(1:length(cir_in)) zeros(1,n_c-length(cir_in))]

FlipMatrix(imp_in) to imp_cir1

Set m from 1 to n_c by 1

LOOP FOR k =1 to length of m by 1

Call subfunction imp_cir2=cirsft(m(k),n_c,imp_cir1)

Set y(k)=imp_cir2*x_inn'

END LOOP

Pseudo-Code of cirsft.m

%%%%%%%%%%%%%%%%%

Subfunction xx=cirsft(mm,nn,in1)

%%%%%%%%%%%%%%%%%

Set in2=in1(nn-rem(mm,nn)+1:nn)

Set xx=[in2 in1(1:nn-rem(mm,nn))]



April, 2002

convolution (function conv in Matlab) would make the prediction error larger because

the zero-valued signal is being predicted from at least some non-zero previous

samples. The conv function is not using previous sample and it assumed zero-value at

the beginning of each section of clip. If the prediction error is too large, the difference

between first sample of current section and last of previous section is very large. A

“tick-tack” sound would appear after grouping at the junction of section. [8]

To minimize the difference of sectors, the overlap-save method of circular

convolution is chosen. It requires the input blocks overlap. Then the input blocks are

circularly convolved with the impulse response. Because of the overlap redundancy at

the input, the circular artifact in the output (the first Nh-1 samples) can simply be

discarded. The following figure illustrates the overlap-save method. [9],[10]

Figure 3.7 Illustration of sound sample, and prediction error for sound which is largest at the end of the section.



April, 2002

Figure 3.8 Block convolution using the overlap-save method. (a) input signal x(n) divided into

overlapping sections, overlap is Nh-1=2, (b) impulse response h(n), (c) output y(n) using direct

convolution, (d) output y1(n) for block circular convolution of x1(n) and h(n), (e) output y2(n), (f) output

y3(n), (g) output y4(n), and (h) sequential concatenation of block outputs after discarding the first two

samples of each block, which is equivalent to the direct convolute ion result. "|" represents

concatenation.



April, 2002

The following conditions are used in the overlap-save convolution:

Total numbers of block is K which was the numbers of measurements in the specified directory

The length of FIR filter (measurements) is M (M=128).

The length of on block of data is L (L>M). It determines by

tsmuasuremen ofnumber signalinput oflength

Each time a block of data of length N=L+M-1 is filtered

Steps of this method are:

(1) Calculating N-point DFT of x (n) and multiplying it with the N-point DFT of h (n).

(2) Calculating N-point IDFT and discarding the first M-1 output sample. The last samples are the desired filter output

(3) Appending the last M-1 samples to the beginning of the new block of signal.

(4) Going to (1) until reach the end of the signal.

L L L

save last M-1 sample

Signal

M-1 zero

output

discard M-1 samples

Figure 3.9 Overlap-save method in this program



April, 2002

The reason for discarding the first (M-1) output samples is that they are the

result of circular convolution. Linear convolution starts at the Mth sample. For the

same reason, the last M-1 samples of the processed block should be appended to the

beginning of the new block

3.2 Input Parameters

The input to the system is a 16 bit, mono wave file. This is also known as “CD

Quality.” The wave data is in Pulse Code Modulation (PCM) format. Each sample of

the signal is represented as a 16 bit signed integer. Provided functions open and read

the data. Data format is assumed that re-sampling at the beginning of function. The

file is read into a dynamically allocated memory buffer.

3.3 Output Parameters

The processing file is a 16 bit, stereo wave sound. It has same sampling rate as

input sound. The maximum HRTF length supports to 128 samples.



April, 2002

Chapter 4 HRTF Results

The following figure is a monaural sound called “GloryBe.wav”. There are two

louder parts. The frequency of it concentrated at 500-700Hz in spectrogram.

The waveform statistics:

Mono Sound

Min Sample Value: -31684

Max Sample Value: 32572

Peak Amplitude: -.05 dB

Possibly Clipped: 0

DC Offset: -.031

Minimum RMS Power: -52.83 dB

Maximum RMS Power: -7.27 dB

Average RMS Power: -18.51 dB

Total RMS Power: -15.76 dB

Using RMS Window of 50 ms

Figure 4.1 Graph of GloryBe.wav and this spectrogram



April, 2002

4.1 Comparison HRTF-sound with common stereo sound

The following wave is created by HRTF-synthesis and the sound come from

right hand side from the origin.

The waveform statistics:

Left Right

Min Sample Value: -16053 -31226

Max Sample Value: 15432 28548

Peak Amplitude: -6.2 dB -.42 dB

Possibly Clipped: 0 0

DC Offset: .006 .006

Minimum RMS Power: -62.78 dB -59.29 dB

Maximum RMS Power: -13.57 dB -7.76 dB

Average RMS Power: -24.76 dB -19.29 dB

Total RMS Power: -22.04 dB -16.44 dB


Figure 4.2 Graph of GloryBe.wav after HRTF processing and its spectrogram



April, 2002

The following wave is created by one application (Cool Edit) that convert a

monaural sound to stereo sound .This stereo wave has similar waveform statistic to

that of HRTF sound:

Left Right



Peak Amplitude: -6.02 dB 0 dB


DC Offset: -.016 -.031






Figure 4.3 Simulation of stereo sound of GloryBe.wav by one application and its spectrogram



April, 2002

Even these two graphs seem to have similar waveform and spectrogram; it can

distinguish by using headphone. The HRTF-based sound is coming from right of the

origin, but the stereo sound created from other application has not explicit direction.

From the spectrogram of the graph, I conclude that the frequencies of sound

wave in both cases were between 500-1000Hz where green or red colour were. It is

similar to the original mono sound.

Figure 4.4 3D surface of the GloryBe.wav in frequency expression



April, 2002

4.2 Wave Statistics from different condition I use “GloryBe.wav” for analysis.

a) The waveform statistics and wave structure of

HRTF-sound flowing from the front to the back:

Left Right





DC Offset: .009 . 008






Figure 4.5

b) The waveform statistics and wave structure of HRTF-sound flowing a cycle:

Left Right

Min Sample Value: -16696 -32768 Figure 4.6 Max Sample Value: 15023 32767


Possibly Clipped 0 7


Minimum RMS Power: -54 dB -57.62 dB







April, 2002

Figure 4.7 Spectrogram of the wave in Figure 4.6 and the above is at elevation 50°

and the bottom is at elevation 0°

From these two spectrograms, one point was stated. The amplitude of energy

of two channels were equivalent when the elevation was 90°, larger energy was

occurred as elevation tend to 0°



April, 2002

c) The waveform statistics and wave structure of HRTF-sound flowing in the front from -40° to 90°

Left Right



Peak Amplitude: -.44 dB -.44 dB


DC Offset: .01 .01






Figure 4.8

d) The waveform statistics and wave structure of HRTF-sound flowing in the right from -40° to 90°

Left Right











Figure 4.9



April, 2002

e) The waveform statistics and wave structure of HRTF-sound flowing in the back -40° to 90°

Left Right



Peak Amplitude: -2.26 dB -2.26 dB








Figure 4.10

f) The waveform statistics and wave structure

of HRTF-sound flowing in the left from -40° to 90°

Left Right Min Sample Value: -32569 -13013


Peak Amplitude: 0 dB -5.71 dB








Figure 4.11



April, 2002

g) The waveform statistics and wave structure of HRTF-sound flowing from the front to the back through the above of head

Left Right



Peak Amplitude: -1.53 dB -1.53 dB


DC Offset: .01 .01






Figure 4.12 h) The waveform statistics and wave structure

of HRTF-sound flowing from the right to the left through the above of head

Left Right





DC Offset: .01 .009






Figure 4.13



April, 2002

From the above figures, I could conclude that:

The amplitudes of HRTF wave concern the direction flow of the wave. If the wave

flows at the left side, the left channel has larger amplitude rather than the right

channel and vice versa.

If the HRTF sound is come from the front or back, the left and right channel have

the same wave’s amplitude.

Sounds process to sound as though they originate from the front of a listener

actually sound like they originate from in back of the listener.

Synthesis of sounds with non-zero elevations is similar.



April, 2002

Chapter 5 User Manual of 3D Simulation

All the scripts must run in Matlab version 6.0 or later. First, users must open Matlab. For example, the working directory is “d:\hrtf”.

To run the GUI script, user should type “HRTF”, and then a window pop-up.

Figure 5.1 Matlab 6.0 first page

Figure 5.2 Initial “HRTF based surround sound “ window



April, 2002

The “HRTF based Surround Sound Window” is designed by GUIDE. The name and descriptions of each item in this window as follows: 1)

It shows current working directory. In this case, the path is “D:\hrtf” 2)

This list box shows all directories and files located in the working directory.

3)

This shows the input file name, when user doubled-clicks the file names in the list box.

4)

This button determines the output file name, if the user inputs the file name by a prompting up window.

5)

This button is used to prompt up another window “Setting Horizontal Surround Sound Parameters

6)

This button is used to prompt up another window “Setting Vertical Surround Sound Parameters



April, 2002

7)

This button reset all parameters stored in memory. User could input their choice more times.

8)

This button uses to process all parameters and output a HRTF-based sound.

9)

This button uses to play the HRTF-based sound. 10)

This button is pressed and then calls up a closing window.

5.1 Setting the input and output file name:

To choose the input file, user only need to press the file in the list box. If user press “Choose Output File Name” button, a pop up window ask user to choose the output file name. The default name is “3D.wav”.

Figure 5.3 Pop-up window for choosing the output file name



April, 2002

After choosing the input and output name, the HRTF-based surround sound window become in the following figure. The input file name is “GloryBe.wav” and output file name is “3D.wav”.

5.2 Setting Parameters of Horizontal Surround

After pressing the “Horizontal Surround” button, the following window calls,

Figure 5.4 “HRTF based surround sound” after choosing input and output file name

Figure 5.5 Initial window of “ Setting Horizontal Surround Sound Parameters”



April, 2002

The name and descriptions of each item in this window as follows: 1, 2)

These parts set the starting and ending azimuth angle. The starting angle is 0°

and ending angle was 180° or 360°.

3)

The slider starts from -40° and ended at 90°. Each click of the bar would

increase the angle in 10°.

4)

This part is updated by the above slider.

5)

This area is inserted a picture that described the path of sound flow.

6)

When the user presses the “Route of Wave” button, it updates the above picture

part.

7)

User presses this “Close” button for closing this window and returning the

parameters to “HRTF-based Surround Sound Window”.



April, 2002

If the user chooses azimuth angle staring from 0° and ending at 360°, elevation angle at 30° and presses “Route of Wave” button, the following window would display:

5.3 Setting Parameters of Vertical Surround After pressing the “Vertical Surround” button, the following window is called,

Figure 5.6 Window of “Setting Horizontal Surround Sound Parameters” after setting parameter

Figure 5.7 Initial window of “Setting Vertical Surround Sound Parameters”



April, 2002

The name and descriptions of each item in this window as follow: 1,2)

&

These pair of radio buttons is which part of parameters should set. 3)

This pop-up menu set the azimuth angle of 0°, 90°, 180°, and 270°. 4)

This pop-up menu set the azimuth angle of 0° to 180° and 90° to 270°. 5)

This area is inserted a picture that described the path of sound flow. 6)

When the user presses the “Route of Wave” button, it updates the above picture part.

7)

This button reset all parameters stored in memory. User could input their choice more times.

8)

User presses this “Close” button for closing this window and returning the parameters to “HRTF-based Surround Sound Window”.



April, 2002

If the user chooses “Special Azimuth Angle” radio button, azimuth angle is 90° and presses “Route of Wave” button, the following window would display:

If the user choose “Semi-Circle azimuth Angle” radio button, azimuth angle starts from 90° and ends at 270° and pressed “Route of Wave” button, the following window would display:

Figure 5.8 Window of “Setting Vertical Surround Sound Parameters” after pressing “Route of Wave”. A picture loaded in the blank box when it chose “Specify azimuth angle”

Figure 5.9 Window of “Setting Vertical Surround Sound Parameters” after pressing “Route of Wave”. A picture loaded in the blank box when choosing “Semi_Circle azimuth angle.



April, 2002

5.4 Processing the parameter When user presses the “Press” button, it calls other script to do HRTF. After

that, it prompts a dialog:

5.5 Close the window Please press the “Close” button to quit the program. “Are you sure you want to

close” box pops up. If clicking “Yes”, all windows closed. Otherwise, no action would get part in.

Figure 5.10 Message box for referencing the completing of processing

Figure 5.11 Message box asking user for choosing the close operation



April, 2002

Chapter 6 Conclusion

6.1 Problems with HRTF-based synthesis of spatial audio

Although it is simple to synthesize HRTF’s to spatial audio, several problems

arise. It is often reported that there is absence of spatially-synthesized sounds -

sounds spatialize near the median plane (0° azimuth angle) sound as though they

existed “inside” the head instead of “outside” it. Sounds process as though they

originated either from the front of a listener or from his back (the so-called “front-back”

confusions) [11]. Synthesis of sounds with non-zero elevations is difficult. Since

everyone has a unique set of HRTF’s. If one listens to a spatialized sound from a

“generalized” HRTF set, one may not perceive the sound in the intended spatial

location [12]. In addition to the problems of sound quality, HRTF-based sound

synthesis encounter several computational challenges, too.

Many researchers believe that the solutions to above problems involve a

deeper understanding of the perceptual structure of HRTF data. By investigating the

structure of HRTF’s, researchers single out the features of HRTF’s, such as peaks

and dips in the magnitude responses and the impulse responses. They also examine

specific spatial parameters, such as azimuth, elevation, and distance. Future spatial

audio synthesis algorithms can help to attain perceptual information and solve

problems in the existing systems.

Auditory localization [17] is still not fully understood, and thus developers can

not make an effective price/performance decisions in the design of spatial audio



April, 2002

systems. Furthermore, developers are often at a loss to explain why systems not

perform effectively.

6.2 Headphones

Most existing spatial audio systems require headphones. For example, one

needs to wears certain headgear to listen to 3-D sounds. Headphones are necessary

because they fix the geometric relationship between physical sound sources (the

headphone drivers) and the ears. They can also eliminate crosstalk between binaural

signals.

6.3 Future Work

A problem with real-time application is time delay (The higher the quality is, the

longer the impulse response is). To solve it, some authors propose hybrid (time

domain - frequency domain) convolution. [18] The current implementation of the

program, it takes approximately an hour as processing time for a 30-second sound

clip. A careful re-implementation of C++ can probably reduce the time on dedicated

hardware and the implementation.

In order to achieve greater realism of simulated sound trajectories, a finer

resolution for available HRTF measures is more preferable. It can be performed

through the lineal interpolation of available data.

Acoustic environment modeling refers to combining 3D spatial location cues

with distance, motion, and ambience cues. It creates a complete simulation of an

acoustic scene. Simulating the acoustical interactions in the natural world, we can



April, 2002

achieve stunningly realistic recreations with the 3D positional control. [16] The Doppler

shift should be taken into account if we deal with large distance variations. [15] This is

because the pitch is changing on the moving object. Finally, reverberation in non-

controlled synthetic environment should consider the frequency-dependent effect of

the medium and the reflecting surfaces. [13], [14], [15]



April, 2002

Appendices

Homepage of my project

The web site address of this project is http://hrtf.bravepages.com/ . Inside the

web page, there are some 3D sounds produced by the HRTF measurements. It likes:

The user also gets the source codes and measurements in another

page. There is a button. Clicking this button to enter the

http://hrtf.bravepages.com/source_code.htm

A prompt window asks to enter password and this password is “fyp2002”.



April, 2002

Pseudo-code of Matlab scripts Pseudo-code of hrtf.m %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

MAINFUNCTION hrtf %% HRTF Application M-file for hrtf.fig

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

IF nargin <= 1 , Then

IF nargin == 0, Then

Set initial_dir equals to current directory

ELSEIF nargin == 1 & exist(varargin{1},'dir')

initial_dir = varargin{1};

ELSE

Error_Message='Input argument must be a valid directory'

Stop the program

ENDIF nargin == 0

Open FIG-file

Generate and store a structure of handles to pass to callbacks

Returns a structure containing the handles of the objects in a figure

Stores the variable data in the figure's application data

Call SUBUNCTION load_listbox(initial_dir)

Call the load_listbox SUBFUNCTION

Return figure handle as first output argument

IF nargout > 0, Then

varargout{1} = fig

ENDIF nargout > 0

ELSEIF ischar(varargin{1})

%% INVOKE NAMED SUBFUNCTION OR CALLBACK

%%

Executed until an error occurs

Display(lasterr)

ENDIF nargin <= 1

%%%%%%%%%%%%%%%%%%%

SUBUNCTION listbox1_Callback

%%%%%%%%%%%%%%%%%%%

IF value of 'SelectionType'in figure1 is 'open'

Get the index value from listbox1 FUNCTION



April, 2002

Get the file name from listbox1 FUNCTION

Set filename = file_list{index_selected}

IF value of sorted_index(index_selected) is 1

Change directory to (filename);

Call Subfunction load_listbox(pwd,handles)

ELSE

[path,name,ext,ver] = fileparts(filename)

Set 'String' parameter of selectedfile equals to [path,name,ext,ver]

ENDIF value of sorted_index(index_selected) is 1

ENDIF value of 'SelectionType'in figure1 is 'open'

%%%%%%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION load_listbox(dir_path)

%%%%%%%%%%%%%%%%%%%%%%%%%%

Add (dir_path) directory to MATLAB's current search path

Change diectory to (dir_path)

Set dir_struct = dir(dir_path)

Set [sorted_names,sorted_index] = sortrows({dir_struct.name}')

Set file_names = sorted_names

Set is_dir = [dir_struct.isdir]

Set sorted_index = [sorted_index]

Stores the variable data in the figure's application data.

Update the current directory name of selected file

%%%%%%%%%%%%%%%%%%%

SUBFUNCTION selectedfile_Callback

%%%%%%%%%%%%%%%%%%%%

Wait for update

%%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION outfile_Callback

%%%%%%%%%%%%%%%%%%%%%%

Wait for update

%%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION savefile_name_Callback

%%%%%%%%%%%%%%%%%%%%%%

Set the output file name, the default name is 3D.wav



April, 2002

%%%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION hori_button_Callback

%%%%%%%%%%%%%%%%%%%%%%%

Subfunction called

Set the verti_button callback inactive

Call Subfunction [val,elevangle]=hori_sur

IF val=1

start_angle=0

END_angle=180

ELSE

start_angle=0

end_angle=360

ENDIF val=1

Set choice =1


%%%%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION verti_button_Callback

%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction called

Set the hori_button callback inactive

pos_size = get(handles.figure1,'Position')

Call Subfunction [verti_choice,verti_val] = verti_sur

Set choice=2


%%%%%%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION varargout = initial_button_Callback

%%%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction called

Initialize the hori_button callback

Initialize the verti_button callback

%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION processing_Callback

%%%%%%%%%%%%%%%%%%%%%

Subfunction called

Set index_selected equals to the 'Value'stroed in listbox1



April, 2002

Set file_list equals to the 'String' stored in listbox1

Set filename = file_list{index_selected}

Set outfile_name equals to the 'String' stored in outfile

%%

IF (choice==1)

Call SUBUNCTION hori_final(start_angle,end_angle,elevangle,filename,outfile_name)

ENDIF choice==1

%%

IF (choice==2)

Call SUBUNCTION verti_final(verti_choice,verti_val,filename,outfile_name)

ENDIF

%%%%%%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION playback_Callback

%%%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction called

Set outfile_name equals to the 'String' stored in outfile

Read the wave file

Play the proceeded wave file

%%%%%%%%%%%%%%%%%%%%%%%

SUBFUNCTION figure1_CloseRequestFcn

%%%%%%%%%%%%%%%%%%%%%%%

Subfunction called

Call SUBUNCTION close_Callback

%%%%%%%%%%%%%%%%%%

SUBFUNCTION close_Callback

%%%%%%%%%%%%%%%%%%

Subfunction called

Call subfunction modaldlg

CASE OF (output from subfunction modaldlg)

'no','cancel' : no action

'yes' : delete the frame(handles.figure1)

ENDCASE



April, 2002

Pseudo-code of verti-sur.m %%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction [verti_choice,verti_val] = verti_sur(varargin)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

IF nargin = 0 or isnumeric(varargin{1}), then LAUNCH GUI

Open FIG-file




Set OrigImageAxes parameters

Set OriginalImage parameters

Position figure

Wait for callbacks to run and window to be dismissed

IF the 'Value' in verti_azim_radio not equal to 0

Set verti_choice=1

Set verti_val= the 'Value' in azim_angle_popup

ENDIF

IF the 'Value' in verti_semi_azim_radio not equal to 0

Set verti_choice=2

Set verti_val= the 'Value' in sc_azim_angle_popup

ENDIF

Delete the figure


INVOKE NAMED SUBFUNCTION OR CALLBACK

TRY %% executed until an error occurs

IF (nargout=0)

FEVAL -- Function evaluation

Set [varargout{1:nargout}] = feval(varargin{:})

ELSE

feval(varargin{:})

ENDIF

CATCH

Display(lasterr)

END

ENDIF



April, 2002

%%%%%%%%%%%%%%%%%

Subfunction load_picture(NewVal)

%%%%%%%%%%%%%%%%%

Subfunction called

IF NewVal=1, then

Set pic_name='verti_0.bmp'

ELSEIF NewVal=2


ELSEIF NewVal=3


ELSEIF NewVal==4


ELSEIF elseif NewVal==5

Set pic_name='verti_semi_0.bmp'

ELSEIF NewVal==6

Set pic_name='verti_semi_90.bmp'

ENDIF

SET I = imshow(pic_name)

Set 'Cdata' in OriginalImage to be I

%%%%%%%%%%%%%%%%%%

Subfunction verti_azim_radio_Callback

%%%%%%%%%%%%%%%%%%

Subfunction called�

Set relevant parameters to be active

Set inrelevant parameters to be inactive

Set off= verti_semi_radio

Call subfunction mutual_exclude(off)

Set NewVal equals to the "Value' of azim_angle_popup


%%%%%%%%%%%%%%%%%%%

Subfunction azim_angle_popup_Callback

%%%%%%%%%%%%%%%%%%%

Subfunction called



April, 2002

%%%%%%%%%%%%%%%%%%%

Subfunction verti_s_azim_text_Callback

%% %%%%%%%%%%%%%%%%%

Subfunction called

%% %%%%%%%%%%%%%%%%%

Subfunction verti_s_elev_text_Callback

%% %%%%%%%%%%%%%%%%%

Subfunction called

%%%%%%%%%%%%%%%%%%%

Subfunction verti_s_elev_range_Callback

%%%%%%%%%%%%%%%%%%%

Subfunction called

%%%%%%%%%%%%%%%%%%%

Subfunction verti_semi_radio_Callback

%%%%%%%%%%%%%%%%%%%

Subfunction called

Set relevant parameters to be active

Set inrelevant parameters to be inactive

Set off= verti_azim_radio

Call subfunction mutual_exclude(off)

Set NewVal equals to the "Value' of sc_azim_angle_popup + 4


%%%%%%%%%%%%%%%%%%%%%

Subfunction sc_azim_angle_popup_Callback

%%%%%%%%%%%%%%%%%%%%%

Subfunction called

%%%%%%%%%%%%%%%%%%%%%

Subfunction verti_sc_azim_text_Callback

%% %%%%%%%%%%%%%%%%%%%

Subfunction called



April, 2002

%%%%%%%%%%%%%%%%%%%

Subfunction verti_sc_elev_text_Callback

%% %%%%%%%%%%%%%%%%%

Subfunction called

%%%%%%%%%%%%%%%%%%%%%%%

Subfunction verti_sc_elev_range_text_Callback

%%%%%%%%%%%%%%%%%%%%%%%

Subfunction called

%%%%%%%%%%%%%%%%%%%

Subfunction verti_reset_button_Callback

%% %%%%%%%%%%%%%%%%%

Set relevant parameters to be activeand irrelevant parameters to be inactive

Set off= verti_semi_radio & verti_azim_radio

Call subfunction mutual_exclude(off), stores the variable data in the figure's application data

%%%%%%%%%%%%%%%%%%

Subfunction mutual_exclude(off)

%% %%%%%%%%%%%%%%%%

Subfunction called

Set the 'Value' in off=0

%%%%%%%%%%%%%%%%%%%

Subfunction verti_close_button_Callback

%% %%%%%%%%%%%%%%%%%

Subfunction called

Resume MATLAB program execution of figure1

% %%%%%%%%%%%%%%%%%%

Subfunction Show_pic_Callback

% %%%%%%%%%%%%%%%%%%

IF the 'Value' in verti_azim_radio not equals to 0

NewVal=the 'Value' in azim_angle_popup

ENDIF

IF the 'Value' in verti_semi_radio not equals to 0

NewVal=the 'Value' in sc_azim_angle_popup + 4

ENDIF

Call the subfunction load_picture(NewVal), stores the variable data in the figure's application data



April, 2002

Pseudo-code of hori_sur.m %%%%%%%%%%%%%%%%%%%%%%

Subfunction [val,elevangle]=hori_sur(varargin)

%%%%%%%%%%%%%%%%%%%%%%


Open FIG-file




Set OrigImageAxes parameters

Set OriginalImage parameters

Position figure

Wait for callbacks to run and window to be dismissed:

Set val equals to the'Value' in hori_end_azim

Set elevangle equals to the 'String' in hori_elev

delete the figure




Display(lasterr)

ENDIF nargin <= 1

%%%%%%%%%%%%%%%%%%

Subfunction load_picture(NewPic)

%%%%%%%%%%%%%%%%%%

Subfunction called

IF NewPic=1, then

Set pic_name='hori_180.bmp'

ELSEIF NewPic=2, then

Set pic_name='hori_360.bmp'

END

Set I= imshow(pic_name)

Set 'Cdata' in OriginalImage to be I

%%%%%%%%%%%%%%%%%%

Subfunction hori_end_azim_Callback

%%%%%%%%%%%%%%%%%%

Subfunction called



April, 2002

%%%%%%%%%%%%%%%%%%

Subfunction hori_elevslider_Callback

%%%%%%%%%%%%%%%%%%

Subfunction called

Set the initial slider value and range

Get the new value for the elev angle from the slider

Set new value to nearest number

Set the 'String' in hori_elev to new value)


%%%%%%%%%%%%%%%%%%

Subfunction hori_elev_Callback

%%%%%%%%%%%%%%%%%%

Subfunction called

%%%%%%%%%%%%%%%%%%%

Subfunction hori_close_button_Callback

%%%%%%%%%%%%%%%%%%%

Subfunction called

Resumes the M-file execution

%%%%%%%%%%%%%%%%%%

Subfunction Show_Pic_Callback

%%%%%%%%%%%%%%%%%%

IF the 'Value' of hori_end_azim=1

Set NewPic=1

ELSE the 'Value' of hori_end_azim=2

Set NewPic=2

ENDIF

Call the subfunction load_picture(NewPic)




April, 2002

Pseudo-code of modaldlg.m %%%%%%%%%%%%%%%%%%%%%

Subfunction answer = modaldlg(varargin)

%%%%%%%%%%%%%%%%%%%%%


Open FIG-file




Position figure

Wait for callbacks to run and window to be dismissed

IF ~ishandle(fig), then

Set answer = 'cancel'

ELSE


Delete the figure

ENDIF




Display(lasterr)

ENDIF nargin <= 1

%%%%%%%%%%%%%%%%

Subfunction noButton_Callback

%%%%%%%%%%%%%%%%

Subfunction called

Set answer = 'no'



%%%%%%%%%%%%%%%%%

Subfunction yesButton_Callback

%%%%%%%%%%%%%%%%%

Subfunction called

Set answer = 'yes'





April, 2002

Pseudo-Code of readhrtf.m

%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction [y] = readhrtf(elevangle,azim,choose_index)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Set ext = '.wav'

IF (choose_index=1) ,then

Call subfunction pathname = hrtfpath(pwd,filesep,'horizontal','H',ext,elevangle,azim,choose_index)

Read (pathname) wave file into [y,fs,nbits]

IF (fs ~= 44100 | nbits ~= 16) ,then

Error message='Incorrect wave file format. Expected 16 bit samples at 44.1 kHz sampling rate.'

ENDIF

ENDIF

IF ((choose_index==2) | (choose_index==3)) , then

Call subfunction pathname = hrtfpath(pwd,filesep,'vertical','H',ext,elevangle,azim,choose_index)

Read (pathname) wave file into [y,fs,nbits]

IF (fs ~= 44100 | nbits ~= 16), then

Error message='Incorrect wave file format. Expected 16 bit samples at 44.1 kHz sampling rate.'

ENDIF

ENDIF

Pseudo-Code of hrtfpath.m

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction [s] = hrtfpath(root,dir_ch,subdir,select,ext,elev,azim,choose_index)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

IF (choose_index=1), then

Set s = sprintf('%s%s%s%selev%d%s%s%de%03da%s', root,dir_ch,subdir,dir_ch,round(elev),...

dir_ch,select,round(elev),round(azim),ext)

ENDIF


Set s = sprintf('%s%s%s%sazim%d%s%s%03de%03da%s',root,dir_ch,subdir,dir_ch,round(azim),...


ENDIF


Set s = sprintf('%s%s%s%sazimsemi%d%s%s%03de%03da%s',root,dir_ch,subdir,dir_ch,round(azim),...


ENDIF



April, 2002

Pseudo-Code of groupfile.m

%%%%%%%%%%%%

Subfunction =group_file

%%%%%%%%%%%%

Input Parameters :

left_blk_lap,right_blk_lap,num_file,choice,start_angle,end_angle,elevangle,verti_gp_index

Output Paramters : first_part,second_part

Check Parameter choice

IF choice=1 and 2, then do horizontal hrtf and vertical hrtf respectively,


Set first_part, second_part= horizontal concatenation of left_blk_lap(i,:) and right_blk_lap(i,:)

END OF FOR LOOP

ENDIF

Pseudo-Code of half_circle.m

%%%%%%%%%%%%%%%%%%%%%%%%

Subfunction [num_file]= half_circle(elevangle,filelist)

%%%%%%%%%%%%%%%%%%%%%%%%

Check elevation angle (-40° to 90°), set num_file refer to particular elevation angle

Pseudo-Code of par_ser.m

%%%%%%%%%%%%%%%%%%%%%%%

Subfunction out_ser=par_ser(input,a,n,b_num)

%%%%%%%%%%%%%%%%%%%%%%%

Set l_r=length(input), z_n=a-1, L=n-z_n

LOOP FOR k=1 to b_num by 1

IF k=1, then

Set r_discard(k,:)=[zeros(1,z_n) input(1:L)]

ELSEIF k=b_num

Set r_end=input((b_num-1)*L+1-z_n:length(input))

Set r_discard(k,:)=[r_end zeros(1,n-length(r_end))]

ELSE

Set r_discard(k,:)=input((k-1)*L+1:(k-1)*L+n)

ENDIF

END LOOP

Set out_ser=r_discard



April, 2002

References [1] Blauret, J. P., Spatial Hearing, Cambridge, MA, MIT Press (1983) [2] Yoichi Haneda, Shoji Makino, Yutaka Kaneda, Nobuhiko Kitawaki. (1999), “Common-

Acoustical-Pole and Zero Modeling of Head-Related Transfer Functions, IEEE Transactions on Speech and Audio Processing, vol 7,no.2, Mar 1999

[3] MATLAB description

http://www.mathworks.com/products/matlab/

[4] HRTF Measurements of a KEMAR Dummy-Head Microphone http://xenia.media.mit.edu/~kdm///hrtf.html

[5] KEMAR (Knowles Electronic Manikin for Acoustic Research) http://www.parmly.luc.edu/parmly/behav_psych_resrch.html [6] Kendall, Gary S. 1995. A 3-D sound primer: Directional hearing and stereo reproduction.

Computer Music Journal 19 (4, Winter): 23-46. [7] Gardner, W.G., K.D. Martin (1995). “HRTF measurements of a KEMAR”, J.Acoust.

Soc.Am.,97(6),pp3907-3908 [8] Linear Prediction Analysis

http://www.en.polyu.edu.hk/~mwmak/notes/BEng_SP/linear_prediction_analysis.ppt

[9] S.K.Mitra, McGraw-Hill,1998, “Digital Signal Processing- A Computer-based Approach” [10] Wataru Mayeda, Prentice Hall Inc., 1993 “ Digital Signal Processing” [11] Wightman, F.L., & Kistler, D.J. (1992) "A model of HRTFs based on principal component

analysis and minimum-phase reconstruction," Journal of the Acoustical Society of America, 91(3), 1637-1647.

[12] Wightman, F.L., & Kistler, D.J. (1989a) "Headphone simulation of free-field listening I:

Stimulus synthesis,"Journal of the Acoustical Society of America, 85(2), 858-867. [13] Gardner, W.G. (1992). “The Acoustic Room”, Master’s thesis, Dept. of Media Arts and

sciences, MIT. [14] Gardner W.G. (1998). “Reverberation Algorithms”, in Applications of Digital Signal

Processing to Audio and Acoustics, Kahrs, M., and K. Brandeburg, Ed., Kluwer Academic, Norwell, MA

[15] Gardner W.G. (1999), “3D Audio and Acoustic Environment Modeling” [16] Begault, D.R. (1994), “3-D Sound for Virtual Reality and Multimedia”, Academic Press,

Cambridge, M.A. [17] Barbara G. Shinn-Cunningham, Nathaniel I. Durlach, Richard M. Held, Massachuetts

Institute of Technology, Cambridge, (March 1998)”Adapting to supernormal auditory localization cues”

[18] . W.G. Gardner, "Efficient convolution withoutinput-output Delay", Presented at the 97th convention of the Audio Engineering Society,San Francisco. Pre-print 3897, 1994

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