A multi-step excited model for speech parameter trajectories

The authors present a new model to characterize the trajectories of the analysis parameters of speech. They represent their evolution as the output of a vector autoregressive system excited by a multistep function, i.e., a sum of an arbitrary number of step-functions. The constant parts of the resulting function represent targets to be attained by the output of the system. Each target corresponds roughly to a speech event. As a new target can arrive before the present one is attained, coarticulation phenomenon can be appropriately treated. Inversely, stable parts of speech are represented by sufficiently spaced targets. Detection of steps and estimated of their amplitudes are performed iteratively by an analysis-by-synthesis method that minimises a quadratic criterion