A comparison of alternative procedures for digital spectral analysis of speech
A. A. Kania, Donald G. Jamieson, Ketan Ramji, Terrance M. Nearey · The Journal of the Acoustical Society of America · 1988
Researchers now enjoy an increasingly wide selection of alternative procedures with which to characterize the time × frequency × amplitude variation in a speech waveform. Spectral analyses using a filter-bank technique, the digital Fourier transform (DFT), and a variety of linear predictive coding (LPC) procedures are now widely available. Approaches using an autoregressive (AR), moving average (MA), auto-regressive moving average (ARMA), or maximum entropy (ME) procedure are already widely available, or are becoming available. The present paper reviews the assumptions of, and the interrelations between, alternative methods, and outlines the relative advantages of the various approaches in providing information about the speech waveform. Finally, the human factors aspects of alternative spectral displays are discussed.