Interaural fluctuations and the detection of interaural incoherence. IV. The effect of compression on stimulus statistics

Abstract

The purpose of this experiment was to determine whether the normalized interaural cross-correlation (CC) model or a model based on interaural phase and level differences can better describe incoherence detection data. The ability to detect interaural incoherence in three sets of reproducible dichotic noises was tested in six listeners. The first set contained noises with a constrained value of the CC and the CC including signal compression. The second set contained noises with a constrained value of the CC including signal compression. The third set contained noises with constrained values in the fluctuations in the interaural differences. Modeling showed that neither the CC model nor the model using the interaural differences could account for the data in any set. Examination of the statistical properties of the stimuli showed that including compression before the calculation of the interaural CC causes a substantial correlation of this metric to the fluctuations in the interaural phase difference. This finding implies that it may be more difficult to discriminate between the common types of binaural models than previously thought.

The role of envelope statistics in detecting changes in interaural correlation

“…The data points represent the arithmetic average of the interaural statistic over the 25 tokens, and the error bars are two standard deviations in overall length. As was shown in previous reports (e.g., Goupell and Hartmann, 2006;Goupell, 2010), stimuli with the same value of the interaural cross-correlation q can have a wide range of values in q PP , s t ðDUÞ, and s t ðDLÞ when the BW is only 10 Hz.…”

“…This is interesting because one might expect listeners to rely solely on ILDs at high frequencies where phase locking cannot follow the fine-structure IPDs in the stimuli. An explanation for this is that the fluctuations in the IPDs and ILDs are not independent for randomly generated noises (Goupell, 2010) and IPDs could be transformed to ILDs at high CFs (van de Par and Kohlrausch, 1998). Envelope weighting was beneficial in the model predictions at 500 and 2000 Hz.…”

“…These two models were shown to produce nearly isomorphic statistics in Goupell (2010), therefore it may not be surprising that both models could describe a majority of the variance in the data.…”

“…The step size of the staircase procedure was a ¼ ffiffiffiffiffiffiffiffiffiffiffiffiffi 1 À q 2 p ¼ 0:4 until the first reversal, 0.2 until the second, 0.1 until the third, and 0.05 for the rest of the staircase. Correlation change detection psychometric functions have been previously measured on an a scale (Goupell, 2010). For the correlation change detection tasks, if listeners could not detect the change in correlation (i.e., had four incorrect answers at Da ¼ Dq ¼ 1), the run was stopped and the JND was recorded as "not determinable."…”

“…Psychological transformations were also included before the calculation of the interaural differences (Goupell and Hartmann, 2007;Goupell, 2010). The first transformation was laterality compression, which compresses the physical interaural difference to a perceptual scale as measured for static IPDs and ILDs by Yost (1981).…”