Interaural correlation sensitivity

Sensitivity to differences in interaural correlation was measured for 1.3-ERB-wide bands of noise using a 2IFC task at six frequencies: 250, 500, 750, 1000, 1250, and 1500 Hz. The sensitivity index, $d^{\prime },$ was measured for discriminations between a number of fixed pairs of correlation values. Cumulative $d^{\prime }$ functions were derived for each frequency and condition. The $d^{\prime }$ for discriminating any two values of correlation may be recovered from the cumulative $d^{\prime }$ function by the difference between cumulative $d^{\prime }’\mathrm{s}$ for these values. Two conditions were employed: the noisebands were either presented in isolation (narrow-band condition) or in the context of broad, contiguous flanking bands of correlated noise (fringed condition). The cumulative $d^{\prime }$ functions showed greater sensitivity to differences in correlation close to 1 than close to 0 at low frequencies, but this difference was less pronounced in the fringed condition. Also, a more linear relationship was observed when cumulative $d^{\prime }$ was plotted as a function of the equivalent signal-to-noise ratio (SNR) in dB for each correlation value, rather than directly against correlation. The equivalent SNR was the SNR at which the interaural correlation in an NoSπ stimulus would equal the interaural correlation of the noise used in the experiment. The maximum cumulative $d^{\prime }$ declined above 750 Hz. This decline was steeper for the fringed than for the narrow-band condition. For the narrow-band condition, the total cumulative $d^{\prime }$ was variable across listeners. All cumulative $d^{\prime }$ functions were closely fitted using a simple two-parameter function. The complete data sets, averaged across listeners, from the fringed and narrow-band conditions were fitted using functions to describe the changes in these parameters over frequency, in order to produce an interpolated family of curves that describe sensitivity at frequencies between those tested. These curves predict the spectra recovered by the binaural system when complex sounds, such as speech, are masked by noise.