Techniques for Noise Robustness in Automatic Speech Recognition

8

Features Based on Auditory Physiology and Perception

Richard M. Stern1, Nelson Morgan2

1Carnegie Mellon University, USA 2International Computer Science Institute and the University of California, Berkeley, USA

8.1 Introduction

It is well known that human speech processing capabilities far surpass the capabilities of current automatic speech recognition and related technologies, despite very intensive research in automated speech technologies in recent decades. Indeed, since the early 1980s, this observation has motivated the development of speech-recognition feature-extraction approaches that are inspired by auditory processing and perception, but it is only relatively recently that these approaches have become effective in their application to computer speech processing. The goal of this chapter is to review some of the major ways in which feature extraction schemes based on auditory processing have facilitated greater speech-recognition accuracy in recent years, as well as to provide some insight into the nature of current trends and future directions in this area.

We begin this chapter with a brief review of some of the major physiological and perceptual phenomena that have motivated feature-extraction algorithms based on auditory processing. We continue with a review and discussion of three seminal “classical” auditory models of the 1980s that have had a major impact on the approaches taken by more recent contributors to this field. Finally, we turn our attention to selected ...