A speech analyzer is described which measures the degree of fit between the energy distribution of any speech signal and a set of “standard” energy distribution patterns stored in the machine. This technique is based on the assumption that a phoneme can be characterized, at least for a single speaker, by specifying the points of energy concentration in the frequency spectrum and by specifying the energy envelope, i.e., energyvstime characteristic, of selected portions of the spectrum. A set of contiguous band filters covering the frequency range 100–7000 cycles/sec are used in combination with rectifiers and integrators to produce polarized signals which are functions of the energy distribution of the speech input signal. Improved selectivity and discrimination against noise and noise‐like signals are obtained by combining the outputs from adjacent filters to measure thedifferencebetween signal levels, and further combining signals to measure thesecond differencebetween signals in adjacent filter bands. “Optimum filters” for phonemes are constructed by adding output signals corresponding to frequencies of energy concentration and subtracting signals corresponding to energy minima; this summation generates a signal proportional to the degree of “fit” between the speech signal and the specified pattern. Separate summations of the low and high frequency filter outputs provide measures of intensity, voiced‐unvoiced detection, and pitch extraction signals. Some results are presented.