A new voice source model based on high-speed imaging and its application to voice source estimation

There are numerous models of varying complexities which seek to efficiently represent the voice source signal. These models are typically based on data and observations which can come from air-flow masks, electroglottographs, mechanical systems, and the inverse-filtering of speech signals. The first part of this study examines observations from the high-speed imaging of the larynx and proposes a new source model, which is shown to provide a better fit for the observed data than existing models. The proposed source model is then used in an automatic source estimation application, based on methods introduced in an earlier study [1]. Results, on average, show that the proposed model provides a more accurate estimation of the source signal compared with the Liljencrants-Fant model.