Abstract
The principal-components method is sometimes employed to describe speech spectra in terms of a small number of factors, that is eigenvectors of the covariance matrix. In this study, this method has been used to analyze the spectral properties of continuous speech and to regenerate the spectra from a small set of factors. Spectral data from 0 to 5000 Hz was obtained using a linear-predictive (LP) all-pole model. This data was used to calculate the average energy in twenty bands, each about an auditory critical bandwidth wide. The analysis was applied to (1) the log-coded band energies and (2) the band energies to the one-third power. Continuous speech was synthesized using spectra computed from a small number of principal-component factors and the LP residual signal. The quality of this speech is compared with speech synthesized using a low-order LP vocoder. In addition, it is argued that the principal components might be more easily identifiable with linguistic categories than are the poles of the low-order LP model.
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