Abstract
This paper describes an implementation of a speaker-independent digit-recognition system. The digit classification scheme is based on segmenting the unknown word into three regions and then making categorical judgments as to which of six broad acoustic classes each segment falls into. The measurements made on the speech waveform include energy, zero crossings, two-pole linear predictive coding analysis, and normalized error of the linear predictive coding analysis. A formal evaluation of the systems showed an error rate of 2.7 percent for a carefully controlled recording environment and a 5.6 percent error rate for on-line recordings in a noisy computer room.
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