A Canonical Representation of Speech

It is well known that usage of an appropriate representation of the speech signal improves the performance of speech coders, recognizers, and synthesizers. In this paper we present a representation of speech that has the efficiency, in terms of being compact, similar to that of parametric modeling, but additionally has the completeness property of signal expansions. The resulting canonical representation of speech is suited for a wide range of speech processing applications and we demonstrate this through experiments related to coding and prosodic modification.