1. A system for taxonomically distinguishing grouped segments of signals captured in unconstrained manner by a transducer for a plurality of sources, the system comprising: (a) a vector construction unit constructing at least one vector of predetermined form for each of the grouped signal segments; (b) a training unit coupled to said vector construction unit, said training unit including: a decomposition portion executing an adaptive sparse transformation upon a joint corpus of vectors for a plurality of signal segments of distinct sources, said decomposition portion generating for each said vector in said joint corpus at least one adaptive decomposition defined on a sparse transformation plane as a coefficient weighted sum of a representative set of decomposition atoms, and, a discriminant reduction portion coupled to said decomposition portion, said discriminant reduction portion being executable to mutually associate decomposition atoms of the representative set in m-wise manner for determining a cooperative strength thereof in distinguishing one distinct source from another, within a multi-dimensional plane, and thereby derive from said representative set at least one optimal combination of atoms for cooperatively distinguishing signals attributable to different ones of the distinct sources, wherein m is greater than or equal to 2; and, (c) a classification unit coupled to said vector construction unit, said classification unit including: a projection portion projecting a spectral vector of an input signal segment onto said sparse transformation plane to generate an adaptive decomposition therefor as a coefficient weighted sum of said representative set of decomposition atoms, and, a classification decision portion coupled to said projection portion, said classification decision portion being executable to discover for said adaptive decomposition of said input signal segment a degree of similarity relative to each of the distinct sources according to the optimal combination, and to thereby determine one of the distinct sources to have generated the input signal segment according to the degree of similarity.
1. A system for taxonomically distinguishing grouped segments of signals captured in unconstrained manner by a transducer for a plurality of sources, the system comprising: (a) a vector construction unit constructing at least one vector of predetermined form for each of the grouped signal segments; (b) a training unit coupled to said vector construction unit, said training unit including: a decomposition portion executing an adaptive sparse transformation upon a joint corpus of vectors for a plurality of signal segments of distinct sources, said decomposition portion generating for each said vector in said joint corpus at least one adaptive decomposition defined on a sparse transformation plane as a coefficient weighted sum of a representative set of decomposition atoms, and, a discriminant reduction portion coupled to said decomposition portion, said discriminant reduction portion being executable to mutually associate decomposition atoms of the representative set in m-wise manner for determining a cooperative strength thereof in distinguishing one distinct source from another, within a multi-dimensional plane, and thereby derive from said representative set at least one optimal combination of atoms for cooperatively distinguishing signals attributable to different ones of the distinct sources, wherein m is greater than or equal to 2; and, (c) a classification unit coupled to said vector construction unit, said classification unit including: a projection portion projecting a spectral vector of an input signal segment onto said sparse transformation plane to generate an adaptive decomposition therefor as a coefficient weighted sum of said representative set of decomposition atoms, and, a classification decision portion coupled to said projection portion, said classification decision portion being executable to discover for said adaptive decomposition of said input signal segment a degree of similarity relative to each of the distinct sources according to the optimal combination, and to thereby determine one of the distinct sources to have generated the input signal segment according to the degree of similarity. 11. The system as recited in claim 1 , wherein none of said signal segments is attributable to a known distinct source prior to the adaptive sparse transformation of the decomposition portion, said decomposition and discriminant reduction portions thereby executing to cluster together similar ones of said segments.