Multipitch estimation and sound separation by the spectral smoothness principle

Abstract

A processing principle is proposed for finding the pitches and separating the spectra of concurrent musical sounds. The principle, spectral smoothness, is used in the human auditory system which separates sounds partly by assuming that the spectral envelopes of real sounds are continuous. Both theoretical and experimental evidence is presented for the vital importance of spectral smoothness in resolving sound mixtures. Three algorithms of varying complexity are described which successfully implement the new principle. In validation experiments, random pitch and sound source combinations were analyzed in a single time frame. The number of simultaneous sounds ranged from one to six, the database comprising sung vowels and 26 musical instruments. Usage of a specific yet straightforward smoothing operation corrected approximately half of the pitch errors that occurred in a system which was otherwise identical but did not use the smoothness principle. In random four-voice mixtures, pitch error rate reduced from 18 % to 8.1 %.