Long Term Analysis-Synthesis of Speech by Non-Stationary AR Methods

The use of non-stationary AR techniques for characterizing segments of speech of relatively long duration (e.g. 0.5 sec., a time duration that may include many bisillabic words) has been recently considered. A method has been proposed for this purpose, based on a non-stationary lattice, representing the dependence on time by a linear combination of functions of a suitable orthogonal basis. An iterative procedure for removing the bias of the formant frequencies due to the fundamental frequency is proposed in connection with the parametric non-stationary estimation of long-term segments of speech. The non-stationary tecnique can be extended to the identification of the excitation source; a method is described for recovering this signal from the residual of the lattice predictor. The efficiency of the resulting analysis-synthesis method is illustrated by real speech examples.