Abstract: A method comprising the steps of performing a linear prediction analysis of a speech signal digitized in a series of frames divided into sub-frames, in order to determine the parameters of a short-term synthesis filter; carrying out an open loop analysis to detect voiced signal frames and determine, for each voice frame, a degree of signal voicing and a long-term prediction delay search interval containing a number of delays depending on the degree of voicing; carrying out a closed-loop predictive analysis of the speech signal to select, for at least some sub-frames of the voiced frames, a long-term prediction delay contained in the search interval and constituting a long-term synthesis filter parameter; and determining a stochastic excitation for each sub-frame, to minimize a perceptually weighted deviation between the speech signal and the stochastic excitation filtered by the long-term and short-term synthesis filters.

Abstract: A linear prediction analysis is performed for each frame of a speech signal to determine the coefficients of a short-term synthesis filter and an open-loop analysis is performed to determine a degree of frame voicing. At least one closed-loop analysis is performed for each sub-frame to determine an excitation sequence which, when applied to the short-term synthesis filter, generates a synthetic signal representative of the speech signal. Each closed-loop analysis uses the impulse response of a filter consisting of the short-term synthesis filter and a perceptual weighting filter, by truncating the impulse response to a truncation length that is no greater than the number of samples per sub-frame and is dependent on the energy distribution of the response and the degree of voicing of the frame.

Abstract: A linear prediction analysis is performed for each frame of a speech signal to determine the coefficients of a short-Term synthesis filter. For each sub-frame, an excitations sequence which, when applied to the short-term synthesis filter generates a synthetic signal representative of the speech signal, is determined by means of an iterative process in which a symmetrical matrix B.sub.n, is gradually built up with each iteration. The matrix B.sub.n is reversed with each iteration by decomposing the pattern B.sub.n =L.sub.n .multidot.R.sub.n.sup.T with L.sub.n =R.sub.n .multidot.K.sub.n where L.sub.n and R.sub.n are triangular matrices and K.sub.n is a diagonal matrix, and matrix L.sub.n has only 1s on its main diagonal.