Algorithm for extraction of pitch and pitch salience from complex tonal signals

TLDR

The procedure is grounded in virtual pitch theory, positing that the overall pitch percept arises from both analytic spectral pitch and holistic virtual pitch, represented by spectral‑pitch and virtual‑pitch patterns that include weighted pitch values. The study presents a method for automatically extracting multiple pitch percepts simultaneously evoked by complex tonal stimuli. Spectral‑pitch patterns are derived through spectral analysis, tonal component extraction, masking effect evaluation, and spectral dominance weighting, while virtual‑pitch patterns are generated from these patterns using an advanced subharmonic coincidence assessment algorithm. Res.

Abstract

A procedure is described for the automatic extraction of the various pitch percepts which may be simultaneously evoked by complex tonal stimuli. The procedure is based on the theory of virtual pitch, and in particular on the principle, that the whole pitch percept is dependent both on analytic listening (yielding spectral pitch), and on holistic perception (yielding virtual pitch). The more or less ambiguous pitch percept governed by these two pitch modes is described by two pitch patterns: the spectral-pitch pattern, and the virtual-pitch pattern. Each of these patterns consists of a number of pitch (height) values, and associated weights, which account for the relative prominence of every individual pitch. The spectral-pitch pattern is constructed by spectral analysis, extraction of tonal components, evaluation of masking effects (masking and pitch shifts), and weighting according to the principle of spectral dominance. The virtual-pitch pattern is obtained from the spectral-pitch pattern by an advanced algorithm of subharmonic coincidence assessment. The procedure is based on a previous algorithm for calculating virtual pitch [E. Terhardt, Hear. Res. 1, 155–182 (1979)], and can be regarded as a generalized and advanced version thereof.