Feature extraction in human speech recognition

Abstract

In 1955 George Miller and Patricia Nicely explored the human speech code and discovered that a five-channel feature code is used to extract phonemes from speech. Their mutual information analysis of the confusion matrices of filtered noisy speech showed that the five channels were virtually independent of each other, accounting for the robustness of speech communication quantified by Miller, Heise, and Lichten in 1951. While the 1955 analysis was a major step forward, it did not lead to practical results, since there are no known methods for extracting these features from the speech. This weakness is the basis of the present research program, to define the signal processing required to robustly extract features from narrow bands of speech. Our emphasis is to work in narrow bands, starting from critical bands. In this paper we discuss the first step of this process, which is to measure (a) the jnd for the detection of speech in noise and (b) the jnd for residue pitch given narrow bands of speech in noise. We have been investigating these features with the ultimate goal of trying to build a speech recognition machine based on distinctive feature signal processing.