Effectiveness of a periodic and aperiodic decomposition method for analysis of voice sources

Abstract

Decomposition of speech into periodic and aperiodic components is useful in analyzing and describing the characteristics of voice sources. Such a decomposition is also useful in controlling the excitation source for synthesis. This paper addresses the issue of decomposition of speech into periodic and aperiodic components in the context of speech production. The effectiveness of a recently proposed algorithm for decomposing speech into these components is examined for analysis of voice sources. Synthetic signals are generated using formant synthesis. Different sources of aperiodicity encountered in normal speech production are considered, using a set of parameters to control the synthetic signals. The sources of aperiodicity studied are: (1) additive pulsed or continuous random noise, and (2) modulation aperiodicities due to variation in the fundamental frequency, jitter, and shimmer. Three types of measures are used to characterize these voices: ratio of energies in the periodic and aperiodic components, perceptual spectral distance, and spectrograms. The results demonstrate the effectiveness of the periodic-aperiodic decomposition algorithm for analyzing aperiodicities for a wide variety of voices, and point out the limitations of the algorithm.