Separately spoken individual words can be automatically recognized using a two-dimensional pattern of spectral density versus a nonlinear time base. The pattern for a given word differs from person to person and must be adaptively learned by the machine for each speaker. Simple circuitry is described that learns a word with a single utterance and recognizes it thereafter. The scheme is potentially economical for the spoken equivalent of key entry of data and data inquiry, and a limited vocabulary of commands to the equipment.