A common sequence of operations in the early stages of most sensory systems is a multiscale transform followed by a compressive nonlinearity. In this paper, we explore the contribution of these operations to the formation of robust and perceptually significant representation in the early auditory system. It is shown that auditory representation of the acoustic spectrum is effectively a self-normalized spectral analysis, i.e., the auditory system computes a spectrum that is divided by a smoothed version of itself. Such a self-normalization induces significant effects such as spectral shape enhancement and robustness against scaling and noise corruption. Examples using synthesized signals and a natural speech vowel are presented to illustrate these results. Furthermore, the characteristics of auditory representation are discussed in the context of several psychoacoustical findings, together with the possible benefits of this model for various engineering applications.