Speech recognition using a strong correlation assumption for the instantaneous spectra

The conventional independence assumption made for the evolving speech spectra is replaced by a strong correlation assumption, which then leads to a new stochastic model. This model implements a nonlinear interpolation between the lower and upper bounds of the joint probability distributions. The advantage of the new model over other correlation-based modelling approaches is that it has a low parameter complexity, the same as that in models based on the independence-assumption. Experiments on a speaker-independent E-set database show the effectiveness of this new modelling approach