Analysis of vibratory states in phonation using spectral features of the electroglottographic signal.

Abstract

The vocal folds can oscillate in several different ways, manifest to practitioners and clinicians as "registers" or "mechanisms," of which the two most often considered are modal voice and falsetto voice. Here these will be taken as instances of different "vibratory states," i.e., distinct quasi-stationary patterns of vibration of the vocal folds. State transitions are common in biomechanical nonlinear oscillators, and they are often abrupt and impossible to predict exactly. Therefore, vibratory states are a source of confounding variation, for instance when acquiring a voice range profile (VRP). In the quest for a state-based, non-invasive VRP, a semi-automatic method based on the short-term spectrum of the electroglottographic (EGG) signal was developed. The method identifies rapid vibratory state transitions, such as the modal-falsetto switch, and clusters the EGG data based on their similarities in the relative levels and phases of the lower frequency components. Productions of known modal and falsetto voice were accurately clustered by a Gaussian mixture model. When mapped into the VRP, this EGG-based clustering revealed connected regions of different vibratory sub-regimes in both modal and falsetto.