Perceptual Evaluation of Acoustic Source Width

DOI : 10.17577/IJERTCONV6IS13211

Download Full-Text PDF Cite this Publication

Text Only Version

Perceptual Evaluation of Acoustic Source Width

Anusha V

Ramaiah Institute of Technology Bengaluru, Karnataka, India

Abstract:- In this work, we examine the effect of inter loudspeaker distance on acoustic source width perception for different frequencies. The inter loudspeaker distance is varied as 0,60,120,180and 240cm.The cut-off frequencies are varied as 1000Hz,2000Hz,4000Hz,8000Hz.The stimuli are presented on a linear loudspeaker array. Three normal hearing listeners rate the perceptual ASW of these stimuli on a scale of ( 0-100 ) using a MUSHRA-type presentation. It show that lesser inter loudspeaker distance produces higher ASW. Thus, through this work ,we develop an experimental methodology to study the large acoustic source width using a linear loudspeaker array in an anechoic setup.

Keywords:- Acoustic source width,ASW,Interaural time difference,Inteaural level difference.

  1. INTRODUCTION

    Acoustic source width perception is multidimensional in nature. Localisation of the source ,its speed ,acceleration, the source width, listener envelopment ,size of the enclosure, nature of the ambience-are some of the spatial attributes a listener can extract through auditory perception. these spatial attributes can be broadly grouped as source attributes and ambience attributes. The auditory perception of the source attributes is influenced by the ambience factors .Focusing on the source attributes ,while localization has been addressed as perception of a point source ,acoustic source width is studied as a continuous integrated perception of many point sources like symphony in orchestra. In contrast to localized sources ,a sense of envelopment is produced by the continuous distributed sources around the listener.

    In this work , we examine the effect of interloudspeaker distance on acoustic source width perception for different freuencies.The interloudspeaker distance is varied as 0,60,120,180and 240cm.the cutoff frequencies are varied as 1000hz,2000hz,4000hz,8000hz.the stimuli is presented on a linear loudspeaker array.three normal hearing listeners rate the perceptual width of the stimuli on a scale of (0-100).

    The human ear can be structurally divided into three parts-the external ear, the middle ear and the inner ear. The external ear simply transmits the signals further into the ear it consists of three parts: the pinna, the ear canal and the tympanic membrane. the pinna is the visible part of the ear and helps in directional hearing by filtering sounds depending on their directions the ear canal amplifies the signals around 3-4 khz because at those frequencies it can be seen as a linear resonator the tympanic membrane ,also called the eardrum

    ,changes the wave signals in the air into mechanical vibrations in the ossicles.

    Fig. 1. Diagram of EAR

    The middle ear consists mainly of the ossicles, there are three bones called malleus, incus and stapes .they conduct the mechanical vibrations further into vibrations in the liquid of the inner ear. Humans perceive sounds coming from different directions and localize the event accordingly the most important cues in accomplishing this are interaural time difference(ITD)and interaural level difference. When the sound travels towards the listener, it arrives first at the ear closer to the sound source and the travels around the head to the opposite ear, this delay is called ITD. From pinna and shoulders affect certain frequencies of the signal in one ear, these affects together cause Inter aural level difference(ILD).

  2. EXPERIMENTAL PROCEDURE ASW perception with noise stimuli

    Fig. 2. Experimental setup for ASW listening test. 'd'= inter loudspeaker distance.

    1. Stimuli synthesis

      The stimuli presented is a narrow band white gaussian Noise of sampling frequency 48khz.the signal is generated using a band pass filter .in signal processing, white noise is a random signal having equal intensity at different frequencies

      ,giving it a constant power spectral density in discrete time

      ,white noise is a discrete signal whose samples are regarded as a sequence of serially uncorrelated random variables with zero mean and finite variance ;a single realization of white noise is a random shock.

    2. Filter design

      The white gaussian noise signal generated is passed through a band pass filter whose centre frequency is varied as 1000hz,2000hz,4000hz,8000hz.the filter order is 250.after the signal is filtered ,the narrow band white gaussian signal is shaped using the ASD(Attack-Sustain Decay)technique in order to not loud the speakers immediately.the above ASD technique can also be done using a Tukey Window function which is given by

      Loudness normalisation GUI

      Fig. 3. Loudness, Normalisation GUI

      The scaling factor to achieve this is given across the corresponding slider .The desired stimuli is obtained as the product of the corresponding and the master scale value .the scaling factor is calculated as follows :

      Say the measured loudness is 60db.we want to scale it up to 63db.an additonal 3db has to be added to the signal.

      10=20log10(s*x)

      Where s is the scaling factor and x is the signal energy.

      The GUI is prepared as follows:-

      Fig. 4. Experimental procedure

      • Objective: To study the effect of interloudspeaker distance d on acoustic source width perception for different cutoff frequencies.

      • Apparatus: Loudspeaker,power amplifier,scarlett 18i20.

      • Procedure: To study the effect of inter loudspeaker distance d on asw for different cutoff frequencies.

      • A white Gaussian noise stimuli is synthesized with sampling frequency=48,000hz. This noise is stored in a .wav file.It is passed through a Tukey window function for Sigmodal attack and decay(y). A bandpass filtered signal of order=250 with different fc are created .(b1,b2,b3,b4)

    C=convolution of y and b1 C1=convolution of y and b2 C2=convolution of y and b3 C3=convolution of y and b4 are created.

    TABLE I. THE STIMULI WITH DIFFERENT FC ARE CREATED.

    Fc hz

    Fl hz

    Fh hz

    D1

    (cm)

    D2

    (cm)

    D3

    (cm)

    D4

    (cm)

    D5

    (cm)

    C

    1000

    800

    1200

    0

    60

    120

    180

    240

    C1

    2000

    1600

    2400

    0

    60

    120

    180

    240

    C2

    4000

    3200

    4800

    0

    60

    120

    180

    240

    C3

    8000

    6400

    9600

    0

    60

    120

    180

    240

  3. RESULTS

    D3

    Listener1

    Listener2

    Fc=1000hz

    D1=distance

    58

    Fc=1000hz

    D1

    60

    1000hz

    D2

    100

    1000hz

    D2

    30

    1000hz

    D3

    35

    1000hz

    10

    1000hz

    D4

    77

    1000hz

    D4

    30

    1000hz

    D5

    12

    1000hz

    D5

    40

    Listener3

    1000hz

    D1

    8

    1000hz

    D2

    3

    1000hz

    D3

    0

    1000hz

    D4

    0

    1000hz

    D5

    25

    TABLE II. THE STIMULI WITH DIFFERENT FC ARE CREATED.

    Listener1

    Listener2

    Listener3

    2000hz

    D1

    9

    2000hz

    D2

    2

    2000hz

    D3

    0

    2000hz

    D4

    16

    2000hz

    D5

    33

  4. CONCLUSIONS

2000hz

D1

0

2000hz

D2

60

2000hz

D3

81

2000hz

D4

42

2000hz

D5

30

2000hz

D1

10

2000hz

D2

20

2000hz

D3

20

2000hz

D4

50

2000hz

D5

40

Through this work we develop an experimental setup and methodology for linear source width study. We have studied the ASW perception for different inter-loud speaker distance with different cut-off frequencies. More experiments need to be performed to study the effect of inter loudspeaker distance on ASW.

REFERENCES

  1. S. Arthi adhithya k r,t. V. Sreenivas, perceptual evaluation of simulated auditory source width expansion , Unpublished

  2. F. Rumsey, Spatial quality evaluation for reproduced sound: Terminology, meaning, and a scene-based paradigm, Journal of the Audio Engineering Society, vol. 50, no. 9, pp. 651 666, 2002

    Listener1

    Listener2

    4000hz

    D1

    10

    4000hz

    D1

    10

    4000hz

    D2

    30

    4000hz

    D2

    77

    4000hz

    D3

    40

    4000hz

    D3

    91

    4000hz

    D4

    30

    4000hz

    D4

    37

    4000hz

    D5

    50

    4000hz

    D5

    57

    Listener3

    4000hz

    D1

    1

    4000hz

    D2

    22

    4000hz

    D3

    5

    4000hz

    D4

    2

    4000hz

    D5

    11

  3. R. Mason and F. Rumsey, An assessment of spatial performance of virtual home theatre algorithms by subjective and objective methods, Audio Engineering Society Preprint, vol. 5137, 2000.

  4. J. Blauert, Spatial hearing. MIT Press, 1997. M. Morimoto, K. Iida, and K. Sakagami, The role of reflections from behind the listener in spatial impression, Applied Acoustics, vol. 62, no. 2, pp. 109 124, 2001.

  5. T. Okano, L. L. Beranek, and T. Hidaka, Relations among interaural cross-correlation coefficient (IACCE), lateral fraction (LFE), and apparent source width (ASW) in concert halls, J. Acoust. Soc. Am., vol. 104, no. 1, pp. 255 265, 1998.

  6. J. Blauert and W. Lindemann, Auditory spaciousness: Some further psychoacoustic analyses, The Journal of the Acoustical Society of America, vol. 80, no. 2, pp. 533 542, 1986.

    Listener3

    Listener1

    8000hz

    D1

    9

    8000hz

    D1

    11

    8000hz

    D2

    8

    8000hz

    D2

    47

    8000hz

    D3

    2

    8000hz

    D3

    29

    8000hz

    D4

    13

    8000hz

    D4

    13

    8000hz

    D5

    20

    8000hz

    D5

    59

    Listener2

    8000hz

    D1

    10

    8000hz

    D2

    40

    8000hz

    D3

    20

    8000hz

    D4

    50

    8000hz

    D5

    30

  7. Jayanth M K Method for the subjective assessment of intermediate quality level of coding systems, ITU-R Recommendation BS.1534-

    1, 2003.

  8. S. Arthi and T. V. Sreenivas, Auditory source width, http://ece.iisc.ernet.in/~arthis/aswperception.html, 2016.

  9. M. Goto, H. Hashiguchi, T. Nishimura, and R. Oka, RWC music database: Popular, classical and jazz music databases, ISMIR, vol. 2, pp. 287 288, 2002.

  10. J. P¨atynen, S. Tervo, and T. Lokki, Simulation of the violin section sound based on the analysis of orchestra performance, in 2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) IEEE, 2011, pp. 173 176.

Leave a Reply