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Earphones are faced with ear canal impedance, which is fundamentally different from direct radiator loudspeakers exposed in a free-field environment. EMA analogous circuits have been developed to model the Bluetooth earphone. On the

design has been significantly enhanced

’s movement. In order to cope

ce the

tracking system based on the detection framework is capable of processing images extremely rapidly with high detection rates. The system is successfully implemented

ent.

basis of this simulation model, the enclosure design of the earphone has been optimized using the SA technique. The SPL response resulting from the optimized

and the 3GPP2 standard has been met.

In this thesis, the adaptive 3D-sound projection screen composed of panel speakers, a video head tracker and an adaptive interpolated CCS is proposed. The system is capable of rendering immersive spatial sound with robustness against listener

with the lateral movement of the listener’s head, we introdu adaptive CCS based on video head tracking technique. The head

on the platform of a laptop computer and a digital signal processor. Experimental results reveal that the proposed system is capable of rendering immersive spatial sound with robustness against listener’s movem

REFERENCES

[1] I. Chun, P. A. Nelson and J. T. Kim

[3] C. H. Choi, H. S. Yoon, “Acoustic

Congress and Exposition on Noise Control Engineering

. S. Kwon and C. H. Choi, “Development of the s

Loudspeaker Distortion Compensation by DSP,” in The

23rd AES Interna

[6] M. R. Bai and R. L. Chen, “Optimal Design of Loudspeaker Systems Based on Sequential Quadratic Programming (SQP),” J. Audio Eng. Soc., Vol. 55, No. 1/2, , “ Numerical models of miniature loudspeakers," in The 32nd International Congress and Exposition on Noise

Control Engineering, Jeju Island, Korea, Aug. 2003.

[2] S. J. Oh, H. R. Lee, S. W. Yoon and J. S. Park, “Study of the Acoustical Properties as a Function of Back Cavity for Loudspeaker,” in The 32nd International

Congress and Exposition on Noise Control Engineering, Jeju Island, Korea, Aug.

2003.

and Vibration Characteristics of a Micro Speaker through the Electro-Magnetic field Analysis,” in The 32nd International , Jeju Island, Korea, Aug.

2003.

[4] S. H. Lee, J. H. Kim, J. T. Kim, O

imulation program to analyze acoustic characteristics of a miniature type loudspeaker,” in The 32nd International Congress and Exposition on Noise

Control Engineering, Jeju Island, Korea, Aug. 2003.

[5] A. Bright, “Simplified

tional Conference, Copenhagen, Denmark, May 2003.

pp. 44-54, 2007.

[7] H. Olson, Acoustical Engineering, Van Nostrand, New York, 1957. Reprinted by Professional Audio Journals, Philadelphia, PA, 1991.

[8] L. L. Beranek, Acoustics, Acoustical Society of America, Woodbury, NY. 1996.

[9] W. M. Leach, Jr., Introduction to Electroacoustics and Audio Amplifier Design, Kendall-Hunt, Dubuque, IA, 2003.

[10] N. Thiele and R. Small, in AES Loudspeaker Anthologies, Vols. 1–3, Audio Engineering Society, New York, 1978, 1984, 1996.

[11] M. R. Bai and J., Liao, “Acoustic Analysis and Design of Miniature Loudspeakers for Mobile Phones,” Audio Engineering Society, Vol. 53, No. 11, pp. 1061-1076, 2005.

[12] L. Ingber, “Simulated annealing: practice versus theory,” Mathematical and

Computer Modelling 18, 11, 29-57 (1993).

[13] 3GPP2 C.S0056-0, “Electro-Acoustic Recommended Minimum Performance Specification for cdma2000 Mobile Stations” (3rd Generation Partnership Project 2, 2005).

[14] ITU-T Recommendation P.57, “Artificial ear” (International Telecommunication

Union, 2006).

[15] Kirkeby, P.A. Nelson, and H. Hamada, “Fast deconvolution of multichannel systems using regularization,” IEEE Trans. Speech and Audio Processing, vol. 6, pp. 189-195, 1998.

[16] W. G. Gardner, “3-D Audio Using Loudspeakers,” Kluwer Academic Publishers, 1998.

[17] J. Rose, P. A. Nelson, B. Rafaely, and T. Takeuchi, “Sweet Spot Size of Virtual Acoustic Imaging Systems at Asymmetric Listener Locations,” J. Acoust. Soc.

Am., vol.112, pp. 1992–2002 (2002).

[18] S. Kim, D. Kong, and S. Jang,” Adaptive Virtual Surround Sound Rendering System for an Arbitrary Listening Position,“ J. Audio Eng. Soc., Vol. 56, No. 4, 2008 April.

[19] P. Viola, M. Jones, “Rapid object detection using boosted cascade of simple features,” Computer Vision and Pattern Recognition, 2001.

Eng. Soc., vol. 37, pp. 3–19, 1989 Jan./Feb.

[21] J. M.

ralization of on-line learning and an application to boosting,” Computational Learning Theory:

Eurocolt 95, Springer-Verlag, pp. 23–37, 1995.

[29] J. Quinlan, “Induction of decision trees,” Machine Learning, 1:81–106, 1986.

Jot, “Etude et re´alization d’un spatialisateur de sons par mode`les physiques et perceptifs,” Ph.D. dissertation, Telecom, Paris, France, 1992.

[22] A. N. Thiele, “Loudspeakers in Vented-boxes: Part II,” Audio Engineering

Society,Vol. 19, No. 6, pp. 471-483 (1971).

[23] A. Schuhmacher, and J. Hald, Sound Source Reconstruction Using Inverse Boundary Element Calculations, J. Acoust. Soc. Am. 113 (2003) 114-127.

[24] O. Kirkeby, P. A. Nelson, and H. Hamada, Fast Deconvolution of Multichannel Systems Using Regularization, IEEE Trans. Speech Audio Processing 6 (1998) 189-194.

[25] L. D. Fielder, Analysis of Traditional and Reverberation-Reducing Methods of Room Equalization, J. Audio Eng. Soc. 51 (2003) 3-26.

[26] IEC 711, “Occluded-ear simulators for the measurement of earphones coupled to the ear by ear inserts”(International Electrotechnical Commission, 1981).

[27] C. A. Poldy, “Headphones,” in Loudspeaker and Headphone Handbook, edited by J. Borwick (Focal Press, London, 1994).

[28] Y. Freund and, R.E. Schapire, “A decision-theoretic gene

Table 1 Experimentally identified lumped-parameters of the microspeaker.

(

ohm

)

RE 31.75

Q

TS 5.96

( )

' 2

E m

R

70.033

Q

ES 15.11

(

mH

)

LE 6.49 10× 2

Q

MS 9.85

( )

m2

S

D 7.07 10× 6 Bl

(

T m

)

0.34

( )

Hz

FS 1100.42 VAS

( )

L 1.85 10× 5

Table 2 The dimensions of the earphone and the parameters of acoustic analogous circuit.

Parameter Value Parameter Value Parameter Value Parameter Value

R

ST 1.67 10× 5 aST

( )

m

1.5 10× 3

M

A4 78.8

C

A4 9 10× 13

R

LK 3.85 10× 5 LST

( )

m 3 10× 3

M

A5 9.4 10× 3

C

A5 1.9 10× 12

M

LK 766.5 aEC

( )

m 1.3 10× 2

M

A6 132.3

C

A6 1.5 10× 12

R

A 2 10× 8 LEC

( )

m 1.45 10× 2

M

A7 983.8

C

A7 2.1 10× 12

M

A 232.69 aAE

( )

m 5 10× 3

M

A8 153.5

C

A8 2.1 10× 12

C

AF 2×1013 LAE

( )

m 1 10× 3

R

A5 5.06 10× 7

R

A7 3.11 10× 7

C

AB 3.5 10× 13

Table 3 Parameters of the optimized design versus the original non-optimized design.

Original Optimal

design(1) design(2) (2)/(1) %

( )

m

aST 1.5 10× 3 2 10× 4 13.33%

( )

m3

V

AF 2.83 10× 8 2.8 10× 8 98.94%

( )

m

LST 3 10× 3 2.9 10× 3 96.67%

( )

m3

V

AB 4.85 10× 8 6 10× 8 123.71%

(a)

(b)

Figure 1. (a) Electro-mechano-acoustical analogous circuit of loudspeaker. (b) Same circuit with acoustical impedance reflecting to mechanical system.

M

1

MS

K = C

R MS

C =

Figure 2. The mechanical system of loudspeaker (M is diaphragm and voice coil mass, k is stiffness of suspension, C is damping factor)

.

RE'

RMS CMS

RE LE

eg BluD

fD=Blic

fD=pDSD

MMD

ic

uD

+

+

-+

-ZAB ZAF

UD=SDu - p +

(a)

(b)

Figure 3. (a) Detailed Electro-mechanical-acoustical analogous circuit of loudspeaker.

(b) Another form of acoustic system.

(a) (b) Figure 4. (a) An acoustic resistance consisting of a fine mesh screen.

(b) Analogous circuit.

Figure 5. (a) Closed volume of air that acts as acoustic compliance.

(b) Analogous circuit.

Figure 6. (a) Cylindrical tube of air which behaves as acoustic mass.

(b) Analogous circuit.

Figure 7. Analogous circuit for radiation impedance on a piston in a infinite baffle.

Analogous circuit for radiation impedance on a piston in a tube.

p

1

+

p

2

+

U

1

U

2

Fig. 8. T-circuit of transmission line

Fig. 9. (a) Perforated sheet of thickness t having holes of radius a spaced a distance (b) Geometry of the narrow slit.

x

1

x

2

H

12

H

21

H

22

H

11

Fig. 10 Schematic diagram showing an audio reproduction system using two-channel stereo loudspeakers. Acoustic transfer functions between the loudspeakers and the listener’s ears are indicated in the figure.

Fig. 11 Schematic diagram including crosstalk canceller and acoustic transfer functions to the listener. The architecture of crosstalk canceller is indicated in the dotted line.

H12

H21

H22

H11

y1 y2

x2

x1

C12

C21

C22

C11

ig. 12 The discrete time inverse filtering problem in block diagram form.

Leakage hole Back cavity

V

AB Speaker

Fig. 13 The sectional drawing of earphone connecting with artificial ear.

Artificial ear

Front cavity

V

AF Duct

IEC 711 simulator Length of duct

L

ST

Radius of duct

a

ST

Ear canal

Microphone

D D D

U =u S p

+

CAF

RST

ZSTA

RLK

Duct

Back cavity

CAB

MLK

1

MA

RA

ZSTB

ZSTA ZAEA

ZAEB

ZAEA

Artificial ear

Leakage hole Front cavity

A IEC 711 B

simulator

Fig. 14 (a)

8

IEC 711 simulator Ear canal

p

ED

Fig. 14. The Bluetooth earphone. (a) The analogous circuit of the acoustical system.

(b) The analogous circuit of IEC 711 simulator connecting with the transmission line.

101 102 103 104 105 30

40 50 60 70 80 90 100 110 120 130

Frequency (Hz)

Sound pressure level (dB)

original simulation original experiment optimal simulation optimal experiment reference

mask

Fig. 15 The measured and simulated SPL responses for the optimal design and the original non-optimal design. The frequency response mask and a central reference curve are also sown in the figure.

Fig. 16. Four types of Rectangular Haar-like features.

Fig. 17. Schematic depiction of a the detection cascade. A series of classifiers are applied to every sub-window. The initial classifier eliminates a large number of negative examples with very little processing. Subsequent layers eliminate additional negatives but require additional computation. After several stages of processing the number of sub-windows have been reduced radically. Further processing can take any form such as additional stages of the cascade (as in our detection system) or an alternative detection system.

Further processing

NO.1 NO.2 NO.3

Reject sub-windows All sub-windows

F

T T

T

F F

Fig. 18. The shuffler filter structure.

-1

-1 1/2

1/2

C

i

+C

c

C

i

-C

c

Fig. 19. The two listener positions are symmetric with each other, where

, and are the acoustic transfer functions between the loudspeakers and the listener’s ears.

Hi2

Hc2

Hc1

H i1

Hi1, Hc1,

Hi2 Hc2

Fig. 20. The arrangement of the adaptive 3D-sound projection screen where the

camera is in the middle of the projection screen. The stereo panel speaker

array of the projection screen is constructed using PU foam panels. The size of

each panel is

33.75 cm×25 cm

.

Fig. 21. The GUI of the head tracking system. The system can detect the face and send the coordinate to the beam steering system.

channel separation

102 103 104

-40 -30 -20 -10 0 10 20

Hz

dB

CCS activated Natural separation

(a)

102 103 104

-40 -30 -20 -10 0 10 20

channel separation

Hz

dB

CCS activated Natural separation

(b)

102 103 104 -40

-30 -20 -10 0 10 20

channel separation

Hz

dB

CCS activated Natural separation

(c)

cm.

Fig. 22. The channel separations. (a) The channel separation when the dummy is at the centerline. (b) The channel separation when the dummy moves rightward 7 (c) The channel separation when the dummy moves rightward 30 cm.

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