Current trends in the search for improvements in well-established technologies imitating human abilities, as speech perception, try to find inspiration in the explanation of certain capabilities hidden in the natural system which are not yet well understood. A typical case is that of speech recognition, where the semantic gap going from spectral time-frequency representations to the symbolic translation into phonemes and words, and the construction of morpho-syntactic and semantic structures find many hidden phenomena not well understood yet. The present chapter is intended to explore some of these facts at a simplifying level under two points of view: that of top-down analysis provided from speech perception, and the symmetric from bottom-up synthesis provided by the biological architecture of auditory pathways. An application-driven design of a Neuromorphic Speech Processing Architecture is presented and its performance analyzed. Simulation details provided by a parallel implementation of the architecture in a supercomputer will be also shown and discussed.