A flow waveform-matched low-dimensional glottal model based on physical knowledge.
The purpose of this study is to explore the possibility for physically based mathematical models of the voice source to accurately reproduce inverse filtered glottal volume-velocity waveforms. A low-dimensional, self-oscillating model of the glottal source with waveform-matching properties is proposed. The model relies on a lumped mechano-aerodynamic scheme loosely inspired by the one- and multimass lumped models. The vocal folds are represented by a single mechanical resonator and a propagation line which takes into account the vertical phase differences. The vocal-fold displacement is coupled to the glottal flow by means of an aerodynamic driving block which includes a general parametric nonlinear component. The principal characteristics of the flow-induced oscillations are retained, and the overall model is able to match inverse-filtered glottal flow signals. The method offers in principle the possibility of performing transformations of the glottal flow by acting on the physiologically based parameters of the model. This is a desirable property, e.g., for speech synthesis applications. The model was tested on a data set which included inverse-filtered glottal flow waveforms of different characteristics. The results demonstrate the possibility of reproducing natural speech waveforms with high accuracy, and of controlling important characteristics of the synthesis such as pitch.