9. The method of claim 8 wherein the deciding steps each include the step of calculating a likelihood statistic l' according to the equation: ##EQU21## where the barred variables are sample means, and var ( ) is the unbiased sample variance.
8. In a speech analysis system for recognizing at least one predetermined keyword in a continuous audio signal, each said keyword being characterized by a template having at least one target pattern, said target patterns having an ordered sequence and each target pattern representing a plurality of short-term power spectra spaced apart in real time, an analysis method comprising the steps of for each target pattern, determining from electrical signals representing plural design set pattern samples x of a said target pattern having elements x.sub.i, a covariance matrix K; determining from said plural design set patterns an expected value vector x; calculating from the covariance matrix K a plurality of eigenvectors e.sub.i having eigenvalues v.sub.i where v.sub.i .gtoreq.v.sub.i +1; repeatedly evaluating electrical signals representing a set of parameters determining a short-term power spectrum of said audio signal within each of a plurality of equal duration sampling intervals, thereby to generate a continuous time ordered sequence of short-term audio power spectrum frames; repeatedly selecting from said sequence of frames, electrical signals representing one first frame and at least one later occurring frame to form a multi-frame pattern y; transforming the electrical signals representing each multi-frame pattern y into electrical signals representing new vectors W, represented as (W.sub.1, W.sub.2, . . ., W.sub.p, R), where EQU W.sub.i =e.sub.i (y-x); p is a positive integer constant less than the number of elements of the pattern y, and R is the reconstruction error statistic and equals ##EQU20## deciding whether each said transformed pattern corresponds to a said first target pattern of a keyword template; for each pattern which, according to said deciding step, corresponds to a said first target pattern of a potential candidate keyword, selecting later occurring short-term power spectra to form later occurring multi-frame patterns; deciding whether said later occurring multi-frame patterns correspond respectively to successive target patterns of said potential candidate keyword template; and identifying electrical signals representing a candidate keyword template when said selected multi-frame patterns correspond respectively to the target patterns of a said keyword template.