Most speech parameter estimation techniques are sensitive to linear distortions introduced by the frequency response of the communication environment. Such linear distortions appear as an additive constant in the log spectrum. RelAtive SpectrAI (RASTA) processing, in which time trajectories of temporal representation of speech are band-pass filtered, makes speech analysis less sensitive to steady-state spectral factors in speech. We describe this approach, compare it to a conventional environment-equalizing blind deconvolution technique, and give experimental results from pilot experiments.