We may average the spectral data in a each frequency-band channel over N time-windows (spectral blurring) thus reducing the amount of detail available for reconstructing the signal. This can be used to "wash out" the detail in a segmented signal and works especially effectively on spikey crackly signals (those with brief, bright peaks). We can do this and also reduce the number of partials (spectral trace & blur) and we may do either of these things in a time-variable manner so that the details of a sequence gradually become blurred or gradually emerge as distinct. (Sound example 3.25).
You can do something like this via the vectral~ object. (the smearing via envelope following) Vectral~ is a vector-based envelope follower and has several different modes.
Looking at the Michael Norris page, it looks like he’s doing something more like sampling a spectral frame every n frames, then interpolating between that and the next one. The part of the implementation that’s not clear is what you do in terms of overlapping frames.