Applies to version: 1.1.0

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wierstorf2013_estimateazimuth - Estimate the perceived azimuth using a binaural model


[phi,phi_std,itd,ild,cfreqs] = wierstorf2013_estimateazimuth(sig,lookup,'fs',44100,'dietz2011')
[phi,phi_std,itd,ild,cfreqs] = wierstorf2013_estimateazimuth(sig,lookup)

Input parameters

sig binaural singal
lookup lookup table to map ITDs to angles (struct)

Output parameters

phi estimated azimuth / deg
phi_std standard deviation of the estimated azimuth / deg
itd calculated ITD (s)
ild calculated ILD (dB)
cfreqs center frequencies of used auditory filters (Hz)


wierstorf2013_estimateazimuth(sig,lookup) uses a binaural model to estimate the perceived direction for a given binaural signal. Therefore, it needs the struct lookup, which maps ITD values to the corresponding angles. This can be created with the itd2angle_lookuptable function. The azimuth values are first calculated for every frequency channel and after that their median is calculated. In this process the different frequency channels could be weighted and outlier could be removed, see the options below. The default setting does not apply any weighting of the frequency channels and removes outlier that deviate more than 30 degree from the median.

wierstorf2013_estimateazimuth accepts the following optional parameters:

'fs',fs Sampling rate
'dietz2011' Use the dietz2011 binaural model to estimate the azimuth value. This is the default.
'lindemann1986' Use the lindemann1986 binaural model to estimate the azimuth value.
 Apply equal weighting of all frequency channels. This is the default behavior.
'rms_weighting' Weight the frequency channels according their rms value of the signal.
 Weight the frequency channels after the empirical curve from Raatgever that has a maximum around 600 Hz. Note, that this works well only for special stimuli.
'remove_outlier' Remove frequency channels from azimuth calculation that deviate more than 30 degree from the median azimuth.
'include_outlier' Use all azimuth values to calculate the median. Note, this can lead to NaN if one of the frequency channels has a NaN as direction.


M. Dietz, S. D. Ewert, and V. Hohmann. Auditory model based direction estimation of concurrent speakers from binaural signals. Speech Communication, 53(5):592--605, 2011. [ DOI | http ]

W. Lindemann. Extension of a binaural cross-correlation model by contralateral inhibition. I. Simulation of lateralization for stationary signals. J. Acoust. Soc. Am., 80:1608--1622, 1986.

J. Raatgever. On the binaural processing of stimuli with different interaural phase relations. PhD thesis, TU Delft, 1980.

R. Stern, A. Zeiberg, and C. Trahiotis. Lateralization of complex binaural stimuli: A weighted-image model. J. Acoust. Soc. Am., 84:156--165, 1988.

H. Wierstorf, A. Raake, and S. Spors. Binaural assessment of multi-channel reproduction. In J. Blauert, editor, The technology of binaural listening, chapter 10. Springer, Berlin--Heidelberg--New York NY, 2013.