Letter: Optimal echo path modelling using chaotic modulated speech

Abstract

AbstractA novel modulating scheme is presented that allows optimal echo path modelling using, real time least mean square (LMS) system identification techniques. The systems of interest are usually based on a class of digital adaptive filters (DAFs). The modelling convergence rate derived from the optimal Wiener weights defines the performance criterion. A novel chaotic based modulation regime utilising the logistic mapping is exploited to whiten the speech power spectral density (PSD) whilst preserving the signal bandwidth requirements. The whitened signal optimises the convergence rate and allows adaptation times to be calculated without a‐priori knowledge of the speech signal's second order statistics. Software simulations are reported for an ensemble of conversational speech realisations and it is shown that the described modulation scheme significantly improves the convergence rate and guarantees optimal modelling independent of the input speech signal statistics. Furthermore, the noise whitened input signal circumvents control supervisory problems usually associated with uncoded speech inputs.