Spectral weights in profile listening

Abstract

The COSS analysis suggested by Berg [B. G. Berg, J. Acoust. Soc. Am. 86, 1743-1746 (1989)] is applied to a profile listening task. The listener's task is to detect an increment in the level of the middle component of an n-component spectrum. The overall level of the components is randomly selected from a 20-dB range on each presentation; thus the detection task is essentially one of detecting a change in spectral shape. To implement the COSS analysis, a small perturbation in level is added to each component of the complex. COSS functions are generated from these perturbations, and the spectral weight that the listener assigns to each component is estimated. Data are reported for n = 3, 5, and 11 components and for perturbations with standard deviations of 0.5, 1, and 2 dB. The estimated weights are similar to those derived for an optimum detector; namely, the level at the signal component is compared with the average level of the nonsignal components. This result supports the view that profile analysis involves an across-channel comparison process. The pattern of weights also provides insight into differences among listeners. In a separate experiment, the spectral weights of a very poor profile listener are estimated, and the pattern of the weights suggests reasons for the inferior detection performance.