THE AUDITORY MODELING TOOLBOX
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EXP_BAUMGARTNER2021 - - Simulations of Baumgartner and Majdak (2021)
Usage
data = exp_baumgartner2021(flag)
Description
exp_baumgartner2021(flag) reproduces figures of the study from Baumgartner and Majdak (2021).
The following flags can be specified
- fig2 shows cue-specific predictions, sensitivities, prediction errors,
- and optimal relative weights in order to best explain the actual externalization ratings. Oracle: prediction errors obtained with the oracle model.
- fig3 displays the prediction errors for all decision strategies,
- optimal cue weights and results for paired combinations.
- hartmann1996 models experiments from Hartmann & Wittenberg (1996; Fig.7-8)
- 1st panel: Synthesis of zero-ILD signals. Only the harmonics from 1 to nprime had zero interaural level difference; harmonics above nprime retained the amplitudes of the baseline synthesis. Externalization scores as a function of the boundary harmonic number nprime. Fundamental frequency of 125 Hz. 2nd panel: Synthesis of signals to test the ISLD hypothesis. Harmonics at and below the boundary retained only the interaural spectral level differences of the baseline synthesis. Higher harmonics retained left and right baseline harmonic levels. Externalization scores as a function of the boundary frequency.
- hassager2016 models experiments from Hassager et al. (2016; Fig.6).
- The mean of the seven listeners perceived sound source location (black) as a function of the bandwidth factor and the corresponding model predictions (colored). The model predictions have been shifted slightly to the right for a better visual interpretation. The error bars are one standard error of the mean.
- baumgartner2017 models experiments from Baumgartner et al. (2017).
- Effect of HRTF spectral contrast manipulations on sound externalization. Externalization scores were derived from paired comparisons via Bradley-Terry-Luce modeling.
- boyd2012 models experiments from Boyd et al. (2012; Fig.1, top).
- Average externalization ratings of 1 talker for NH participants against mix point as a function of microphone position (ITE/BTE) and frequency response (BB/LP). The reference condition (ref) is the same as ITE/BB. Error bars show SEM.
Requirements:
- SOFA API v0.4.3 or higher from http://sourceforge.net/projects/sofacoustics for Matlab (in e.g. thirdparty/SOFA)
- Data in hrtf/baumgartner2017
- Statistics Toolbox for Matlab (for some of the figures)
Examples:
To display indivdual predictions for all experiments use
exp_baumgartner2021('fig2');
This code produces the following output:
hartmann1996, Exp. 1
Showing modelling details for hartmann1996_exp1
S_cue Error Weight Description
_________ _________ _______ ______________________________________________________________________________________
MSS 0.073828 0.081818 0 'Monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISS 0.88369 0.011274 0 'Interaural spectral shape (c.f., Hassager et al., 2016)'
MSSD 0.021484 0.042295 0 'Spectral SD of monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISSD 0.62119 0.052943 0 'Spectral SD of interaural spectral differences (c.f., Georganti et al., 2013)'
ITIT 0.79141 0.0035124 0.69234 'Interaural time-intensity trading (ITD vs. ILD)'
IC 0.0083008 0.0047487 0.18995 'Interaural coherence (c.f., Hassager et al., 2017)'
MI 0.0038086 0.012103 0.11771 'Monaural intensity difference (target - reference)'
Oracle NaN 0.0038405 NaN 'Weighted combination'
Showing cue contributions for hartmann1996_exp1
MSS ISS MSSD ISSD ITIT IC MI Error_Oracle Error_WSM Error_LTA Error_MTA Error_WTA BIC_Oracle BIC_WSM BIC_LTA BIC_MTA BIC_WTA
________ ___ ________ ____ _______ _______ _______ ____________ _________ _________ _________ _________ __________ ________ _______ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 0.071595 0 0.084639 0 0.13799 0.58691 0.11886 0.0060689 0.023193 0.016062 0.027608 0.022957 -2.9907 3.7126 -9.3905 -6.6822 -7.6045
MSS, ISS, MSSD, ISSD, ITIT, IC 0 0 0.26045 0 0.11771 0.62184 NaN 0.0057589 0.020118 0.0084312 0.010345 0.010972 -6.4718 -0.21745 -14.222 -13.2 -12.905
MSS, ISS, ISSD, ITIT, IC 0.21613 0 NaN 0 0.1357 0.64817 NaN 0.008223 0.023686 0.026913 0.04029 0.049354 -7.9097 -2.62 -10.028 -8.011 -6.9965
MSS, ISS, ISSD, ITIT 0.46307 0 NaN 0 0.53693 NaN NaN 0.017392 0.029709 0.007816 0.010933 0.02827 -7.3832 -4.706 -17.82 -16.142 -11.392
MSS, ISSD, ITIT 0.46315 NaN NaN 0 0.53685 NaN NaN 0.017392 0.031557 0.0065232 0.027969 0.036925 -10.602 -7.6232 -20.334 -13.055 -11.666
MSS, ITIT 0.46309 NaN NaN NaN 0.53691 NaN NaN 0.017392 0.034445 0.0035632 0.010957 0.018707 -13.821 -10.404 -24.967 -19.35 -16.675
MSS 1 NaN NaN NaN NaN NaN NaN 0.091699 0.091699 0.081818 0.081818 0.081818 -8.7273 -8.7273 -10.907 -10.907 -10.907
hartmann1996, Exp. 2
Showing modelling details for hartmann1996_exp2
S_cue Error Weight Description
__________ __________ ________ ______________________________________________________________________________________
MSS 0.12051 0.0019367 0.019309 'Monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISS 0.00019531 0.063476 0 'Interaural spectral shape (c.f., Hassager et al., 2016)'
MSSD 0.019629 0.010901 0.34659 'Spectral SD of monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISSD 0.0069336 0.017217 0.032649 'Spectral SD of interaural spectral differences (c.f., Georganti et al., 2013)'
ITIT 0.00078125 0.0035481 0.4388 'Interaural time-intensity trading (ITD vs. ILD)'
IC 0.0012695 0.0049122 0.16266 'Interaural coherence (c.f., Hassager et al., 2017)'
MI 4.8828e-05 0.04627 0 'Monaural intensity difference (target - reference)'
Oracle NaN 0.00029003 NaN 'Weighted combination'
Showing cue contributions for hartmann1996_exp2
MSS ISS MSSD ISSD ITIT IC MI Error_Oracle Error_WSM Error_LTA Error_MTA Error_WTA BIC_Oracle BIC_WSM BIC_LTA BIC_MTA BIC_WTA
_______ ___ ______ _______ ____ ________ ________ ____________ _________ __________ _________ _________ __________ ________ _______ _______ ________
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 0.66081 0 0.2029 0 0 0.093239 0.043051 0.016603 0.068566 0.010188 0.013991 0.22396 3.0155 8.6883 -8.6419 -7.3733 3.719
MSS, ISS, MSSD, ISSD, ITIT, IC 0.87483 0 0 0 0 0.12517 NaN 0.0056494 0.065774 0.0018328 0.002641 0.17217 -4.0693 5.7494 -16.89 -15.429 1.2807
MSS, ISS, ISSD, ITIT, IC 0.80456 0 NaN 0.19544 0 0 NaN 0.013594 0.066128 0.0001728 0.0038704 0.2513 -3.3296 2.9983 -27.722 -15.286 1.4071
MSS, ISS, ISSD, ITIT 1 0 NaN 0 0 NaN NaN 0.0026579 0.056353 5.5574e-09 0.017156 0.20467 -12.63 -0.41409 -70.487 -10.716 -0.80029
MSS, ISSD, ITIT 1 NaN NaN 0 0 NaN NaN 0.0026579 0.030535 0.0013744 0.0017853 0.035254 -15.403 -5.6378 -22.2 -21.154 -9.2218
MSS, ITIT 1 NaN NaN NaN 0 NaN NaN 0.0026579 0.024436 0.0015726 0.0013143 0.0035481 -18.176 -9.3016 -23.047 -23.765 -19.793
MSS 1 NaN NaN NaN NaN NaN NaN 0.0026579 0.0026579 0.0019367 0.0019367 0.0019367 -20.948 -20.948 -23.601 -23.601 -23.601
hassager2016
Showing modelling details for hassager2016
S_cue Error Weight Description
_________ _________ ________ ______________________________________________________________________________________
MSS 0.2293 0.0053458 0.57534 'Monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISS 0.33135 0.0047244 0.36112 'Interaural spectral shape (c.f., Hassager et al., 2016)'
MSSD 0.12402 0.088551 0 'Spectral SD of monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISSD 0.15986 0.025814 0.025209 'Spectral SD of interaural spectral differences (c.f., Georganti et al., 2013)'
ITIT 0.14082 0.035836 0.038331 'Interaural time-intensity trading (ITD vs. ILD)'
IC 0.035156 0.13813 0 'Interaural coherence (c.f., Hassager et al., 2017)'
MI 0.0003418 0.19711 0 'Monaural intensity difference (target - reference)'
Oracle NaN 0.0028219 NaN 'Weighted combination'
Showing cue contributions for hassager2016
MSS ISS MSSD ISSD ITIT IC MI Error_Oracle Error_WSM Error_LTA Error_MTA Error_WTA BIC_Oracle BIC_WSM BIC_LTA BIC_MTA BIC_WTA
_______ _______ ____ ________ _______ ___ ___ ____________ _________ _________ _________ _________ __________ _______ _______ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 0.39849 0.40698 0 0.085589 0.10894 0 0 0.0032588 0.016475 0.0066971 0.011033 0.20723 -82.706 -47.056 -88.496 -77.513 -12.989
MSS, ISS, MSSD, ISSD, ITIT, IC 0.29948 0.60597 0 0.076443 0.01811 0 NaN 0.0029749 0.024953 0.0039253 0.0081372 0.077533 -90.893 -44.104 -103.34 -87.303 -37.709
MSS, ISS, ISSD, ITIT, IC 0.26084 0.64136 NaN 0.097809 0 0 NaN 0.0029383 0.015921 0.0035608 0.002736 0.072175 -97.348 -60.173 -108.58 -114.37 -42.375
MSS, ISS, ISSD, ITIT 0.26542 0.64531 NaN 0.089275 0 NaN NaN 0.0029362 0.0042859 0.0029754 0.0026254 0.051861 -103.55 -95.225 -115.62 -118.37 -52.738
MSS, ISSD, ITIT 0.64931 NaN NaN 0 0.35069 NaN NaN 0.0042231 0.0047078 0.0084647 0.0037099 0.038776 -101.73 -99.341 -95.708 -113.86 -62.226
MSS, ITIT 0.64936 NaN NaN NaN 0.35064 NaN NaN 0.0042231 0.0049458 0.0029154 0.0060224 0.038461 -107.91 -104.44 -122.25 -106.29 -65.496
MSS 1 NaN NaN NaN NaN NaN NaN 0.021879 0.021879 0.0053458 0.0053458 0.0053458 -77.907 -77.907 -112 -112 -112
baumgartner2017
Showing modelling details for baumgartner2017
S_cue Error Weight Description
________ ________ _______ ______________________________________________________________________________________
MSS 0.087988 0.036517 0.56054 'Monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISS 0.4207 0.081148 0 'Interaural spectral shape (c.f., Hassager et al., 2016)'
MSSD 0.39395 0.036857 0.10583 'Spectral SD of monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISSD 0.50117 0.051565 0 'Spectral SD of interaural spectral differences (c.f., Georganti et al., 2013)'
ITIT 0.022559 0.13844 0 'Interaural time-intensity trading (ITD vs. ILD)'
IC 0.018164 0.062149 0.33363 'Interaural coherence (c.f., Hassager et al., 2017)'
MI 0.11279 0.12654 0 'Monaural intensity difference (target - reference)'
Oracle NaN 0.023715 NaN 'Weighted combination'
Showing cue contributions for baumgartner2017
MSS ISS MSSD ISSD ITIT IC MI Error_Oracle Error_WSM Error_LTA Error_MTA Error_WTA BIC_Oracle BIC_WSM BIC_LTA BIC_MTA BIC_WTA
_______ _________ ____ _________ ________ ________ ___ ____________ _________ _________ _________ _________ __________ ________ _________ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 0.64838 0.012149 0 0.24297 0.020725 0.075782 0 0.031103 0.039787 0.076446 0.028399 0.14665 4.9692 5.7079 -0.023211 -2.9939 1.9311
MSS, ISS, MSSD, ISSD, ITIT, IC 0.60633 0.0081455 0 0 0 0.38552 NaN 0.025641 0.036983 0.025604 0.027244 0.1235 2.1926 3.2915 -4.4033 -4.217 0.31718
MSS, ISS, ISSD, ITIT, IC 0.66296 0 NaN 0.0054617 0 0.33157 NaN 0.025251 0.035843 0.048979 0.018166 0.11406 -0.05053 1.0003 -3.556 -6.5316 -1.02
MSS, ISS, ISSD, ITIT 0.77099 0 NaN 0.22901 0 NaN NaN 0.031347 0.047592 0.051862 0.029359 0.14939 -1.599 -0.34634 -4.4831 -6.19 -1.3092
MSS, ISSD, ITIT 0.77103 NaN NaN 0.22897 0 NaN NaN 0.031347 0.068016 0.032103 0.032686 0.12457 -3.7963 -1.4724 -7.0206 -6.9666 -2.9528
MSS, ITIT 1 NaN NaN NaN 0 NaN NaN 0.045874 0.075326 0.030911 0.048796 0.13084 -4.8511 -3.3633 -8.2327 -6.8631 -3.9041
MSS 1 NaN NaN NaN NaN NaN NaN 0.045874 0.045874 0.036517 0.036517 0.036517 -7.0484 -7.0484 -8.8313 -8.8313 -8.8313
boyd2012
Showing modelling details for boyd2012
S_cue Error Weight Description
________ ________ _______ ______________________________________________________________________________________
MSS 0.18057 0.042443 0.24038 'Monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISS 0.44687 0.028343 0.30127 'Interaural spectral shape (c.f., Hassager et al., 2016)'
MSSD 0.054395 0.10339 0 'Spectral SD of monaural positive spectral gradients (c.f., Baumgartner et al., 2014)'
ISSD 0.24404 0.032469 0 'Spectral SD of interaural spectral differences (c.f., Georganti et al., 2013)'
ITIT 0.54668 0.040747 0 'Interaural time-intensity trading (ITD vs. ILD)'
IC 0.36709 0.050289 0.30942 'Interaural coherence (c.f., Hassager et al., 2017)'
MI 0.15518 0.082215 0.14893 'Monaural intensity difference (target - reference)'
Oracle NaN 0.01466 NaN 'Weighted combination'
Showing cue contributions for boyd2012
MSS ISS MSSD ISSD ITIT IC MI Error_Oracle Error_WSM Error_LTA Error_MTA Error_WTA BIC_Oracle BIC_WSM BIC_LTA BIC_MTA BIC_WTA
_______ _______ _______ ____ ________ ___ ___ ____________ _________ _________ _________ _________ __________ _______ _______ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 0.20981 0.63629 0.11231 0 0.041592 0 0 0.024676 0.04091 0.22043 0.029526 0.070926 -32.098 -21.987 -9.2732 -49.479 -31.952
MSS, ISS, MSSD, ISSD, ITIT, IC 0.18965 0.63326 0.13451 0 0.042584 0 NaN 0.024621 0.043919 0.028489 0.063165 0.092708 -38.134 -26.559 -53.19 -37.266 -29.592
MSS, ISS, ISSD, ITIT, IC 0.24005 0.68964 NaN 0 0.070312 0 NaN 0.026501 0.043818 0.032461 0.02756 0.055326 -42.654 -32.597 -53.576 -56.849 -42.912
MSS, ISS, ISSD, ITIT 0.23999 0.69008 NaN 0 0.06993 NaN NaN 0.026501 0.032026 0.059887 0.024031 0.044368 -48.645 -44.858 -44.323 -62.586 -50.322
MSS, ISSD, ITIT 0.48914 NaN NaN 0 0.51086 NaN NaN 0.033391 0.036857 0.02862 0.0302 0.046264 -50.015 -48.04 -62.086 -61.011 -52.48
MSS, ITIT 0.48905 NaN NaN NaN 0.51095 NaN NaN 0.033391 0.037232 0.02924 0.026657 0.04717 -56.007 -53.829 -64.653 -66.502 -55.089
MSS 1 NaN NaN NaN NaN NaN NaN 0.052145 0.052145 0.042443 0.042443 0.042443 -53.083 -53.083 -60.196 -60.196 -60.196
To display results for different decision strategies use
exp_baumgartner2021('fig3');
This code produces the following output:
Prediciton errors for tested decisions:
RMSE_WSM RMSE_LTA RMSE_MTA RMSE_WTA BIC_WSM BIC_LTA BIC_MTA BIC_WTA
________ ________ ________ ________ _______ _______ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 0.11786 0.26976 0.18126 0.44556 -175.09 -113.58 -156.52 -59.386
MSS, ISS, MSSD, ISSD, ITIT, IC 0.11746 0.25919 0.17442 0.34271 -183.43 -121.89 -164.66 -91.72
MSS, ISS, ISSD, ITIT, IC 0.11746 0.25839 0.15922 0.28616 -191.41 -126.21 -178.5 -115.19
MSS, ISS, ISSD, ITIT 0.11746 0.26063 0.16057 0.21795 -199.39 -129.27 -181.58 -148.58
MSS, ISSD, ITIT 0.1253 0.27192 0.18598 0.21488 -200.39 -128.68 -169.7 -154.1
MSS, ITIT 0.13732 0.28134 0.18255 0.20226 -198.47 -128.99 -175.7 -164.63
MSS 0.1456 0.1456 0.1456 0.1456 -200.12 -204.11 -204.11 -204.11
WSM weights/percentages
MSS ISS MSSD ISSD ITIT IC MI RMSE BIC
_______ _______ ____ ________ _________ ___ ________ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 0.59174 0.30018 0 0.055064 0.026457 0 0.026563 0.11786 -175.09
MSS, ISS, MSSD, ISSD, ITIT, IC 0.59433 0.32884 0 0.069708 0.0071173 0 NaN 0.11746 -183.43
MSS, ISS, ISSD, ITIT, IC 0.59443 0.32873 NaN 0.069721 0.0071216 0 NaN 0.11746 -191.41
MSS, ISS, ISSD, ITIT 0.59436 0.32883 NaN 0.069703 0.0071109 NaN NaN 0.11746 -199.39
MSS, ISSD, ITIT 0.70682 NaN NaN 0.25484 0.038333 NaN NaN 0.1253 -200.39
MSS, ITIT 0.85482 NaN NaN NaN 0.14518 NaN NaN 0.13732 -198.47
MSS 1 NaN NaN NaN NaN NaN NaN 0.1456 -200.12
LTA weights/percentages
MSS ISS MSSD ISSD ITIT IC MI RMSE BIC
______ ______ ______ ______ ______ ______ ______ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 16.667 20.37 1.8519 7.4074 37.037 12.963 3.7037 0.26976 -113.58
MSS, ISS, MSSD, ISSD, ITIT, IC 12.963 22.222 5.5556 5.5556 40.741 12.963 NaN 0.25919 -121.89
MSS, ISS, ISSD, ITIT, IC 12.963 31.481 NaN 9.2593 31.481 14.815 NaN 0.25839 -126.21
MSS, ISS, ISSD, ITIT 12.963 25.926 NaN 12.963 48.148 NaN NaN 0.26063 -129.27
MSS, ISSD, ITIT 20.37 NaN NaN 16.667 62.963 NaN NaN 0.27192 -128.68
MSS, ITIT 33.333 NaN NaN NaN 66.667 NaN NaN 0.28134 -128.99
MSS 100 NaN NaN NaN NaN NaN NaN 0.1456 -204.11
MTA weights/percentages
MSS ISS MSSD ISSD ITIT IC MI RMSE BIC
______ ______ ______ ______ ______ ______ ______ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 33.333 12.963 9.2593 20.37 9.2593 11.111 3.7037 0.18126 -156.52
MSS, ISS, MSSD, ISSD, ITIT, IC 31.481 12.963 16.667 31.481 3.7037 3.7037 NaN 0.17442 -164.66
MSS, ISS, ISSD, ITIT, IC 27.778 16.667 NaN 25.926 16.667 12.963 NaN 0.15922 -178.5
MSS, ISS, ISSD, ITIT 40.741 29.63 NaN 22.222 7.4074 NaN NaN 0.16057 -181.58
MSS, ISSD, ITIT 33.333 NaN NaN 50 16.667 NaN NaN 0.18598 -169.7
MSS, ITIT 87.037 NaN NaN NaN 12.963 NaN NaN 0.18255 -175.7
MSS 100 NaN NaN NaN NaN NaN NaN 0.1456 -204.11
WTA weights/percentages
MSS ISS MSSD ISSD ITIT IC MI RMSE BIC
______ ______ ______ ______ ______ ______ ______ _______ _______
MSS, ISS, MSSD, ISSD, ITIT, IC, MI 25.926 3.7037 9.2593 3.7037 3.7037 7.4074 46.296 0.44556 -59.386
MSS, ISS, MSSD, ISSD, ITIT, IC 20.37 3.7037 33.333 0 7.4074 35.185 NaN 0.34271 -91.72
MSS, ISS, ISSD, ITIT, IC 31.481 12.963 NaN 14.815 12.963 27.778 NaN 0.28616 -115.19
MSS, ISS, ISSD, ITIT 55.556 14.815 NaN 16.667 12.963 NaN NaN 0.21795 -148.58
MSS, ISSD, ITIT 61.111 NaN NaN 27.778 11.111 NaN NaN 0.21488 -154.1
MSS, ITIT 75.926 NaN NaN NaN 24.074 NaN NaN 0.20226 -164.63
MSS 100 NaN NaN NaN NaN NaN NaN 0.1456 -204.11
Contributions and Prediction errors:
MSS ISS MSSD ISSD ITIT IC MI WSM_RMSE CI_low CI_high
_______ _______ ________ _______ ________ ________ ________ ________ ________ _______
0.59938 0.40062 NaN NaN NaN NaN NaN 0.11809 0.095138 0.15122
0.71892 NaN NaN 0.28108 NaN NaN NaN 0.12576 0.10422 0.15793
0.85482 NaN NaN NaN 0.14518 NaN NaN 0.13732 0.10948 0.1766
0.92907 NaN NaN NaN NaN NaN 0.07093 0.14268 0.10912 0.20868
0.94641 NaN NaN NaN NaN 0.053586 NaN 0.14426 0.11123 0.19873
0.95871 NaN 0.041292 NaN NaN NaN NaN 0.14507 0.11242 0.20648
NaN 0.82733 0.17267 NaN NaN NaN NaN 0.16374 0.11605 0.24185
NaN 0.89015 NaN NaN NaN 0.10985 NaN 0.16868 0.11486 0.25048
NaN 0.90091 NaN NaN NaN NaN 0.099093 0.16892 0.11857 0.24599
NaN 0.92248 NaN NaN 0.077521 NaN NaN 0.17229 0.12508 0.2655
NaN 0.8758 NaN 0.1242 NaN NaN NaN 0.1725 0.11671 0.24754
NaN NaN NaN 0.78507 0.21493 NaN NaN 0.21693 0.17414 0.28489
NaN NaN 0.20616 0.79384 NaN NaN NaN 0.21723 0.17219 0.27164
NaN NaN NaN 0.87082 NaN 0.12918 NaN 0.22133 0.17412 0.28127
NaN NaN NaN 0.92823 NaN NaN 0.071767 0.22439 0.17918 0.28468
NaN NaN 0.48886 NaN 0.51114 NaN NaN 0.23711 0.19133 0.30087
NaN NaN NaN NaN 0.61174 0.38826 NaN 0.26809 0.212 0.34092
NaN NaN NaN NaN 0.64537 NaN 0.35463 0.26855 0.21229 0.32877
NaN NaN 0.59676 NaN NaN 0.40324 NaN 0.2692 0.22905 0.32112
NaN NaN 0.69367 NaN NaN NaN 0.30633 0.29922 0.25709 0.34991
NaN NaN NaN NaN NaN 0.73255 0.26745 0.37218 0.29163 0.44536
Sensitivities:
MSS ISS MSSD ISSD ITIT IC MI
_______ _______ ________ _______ _______ _______ _______
0.20029 0.51084 NaN NaN NaN NaN NaN
0.20029 NaN NaN 0.24854 NaN NaN NaN
0.20029 NaN NaN NaN 0.49307 NaN NaN
0.20029 NaN NaN NaN NaN NaN 0.14482
0.20029 NaN NaN NaN NaN 0.33066 NaN
0.20029 NaN 0.080273 NaN NaN NaN NaN
NaN 0.51084 0.080273 NaN NaN NaN NaN
NaN 0.51084 NaN NaN NaN 0.33066 NaN
NaN 0.51084 NaN NaN NaN NaN 0.14482
NaN 0.51084 NaN NaN 0.49307 NaN NaN
NaN 0.51084 NaN 0.24854 NaN NaN NaN
NaN NaN NaN 0.24854 0.49307 NaN NaN
NaN NaN 0.080273 0.24854 NaN NaN NaN
NaN NaN NaN 0.24854 NaN 0.33066 NaN
NaN NaN NaN 0.24854 NaN NaN 0.14482
NaN NaN 0.080273 NaN 0.49307 NaN NaN
NaN NaN NaN NaN 0.49307 0.33066 NaN
NaN NaN NaN NaN 0.49307 NaN 0.14482
NaN NaN 0.080273 NaN NaN 0.33066 NaN
NaN NaN 0.080273 NaN NaN NaN 0.14482
NaN NaN NaN NaN NaN 0.33066 0.14482
References:
A. W. Boyd, W. M. Whitmer, J. J. Soraghan, and M. A. Akeroyd. Auditory externalization in hearing-impaired listeners: The effect of pinna cues and number of talkers. J. Acoust. Soc. Am., 131(3):EL268--EL274, 2012. [ DOI | arXiv | www: ]
W. M. Hartmann and A. Wittenberg. On the externalization of sound images. J. Acoust. Soc. Am., 99(6):3678--88, June 1996. [ http ]
H. G. Hassager, F. Gran, and T. Dau. The role of spectral detail in the binaural transfer function on perceived externalization in a reverberant environment. J. Acoust. Soc. Am., 139(5):2992--3000, 2016. [ DOI | arXiv | www: ]
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