A probabilistic framework for optimum speech extrapolation in digital mobile radio

In digital mobile radio systems the speech quality can be degraded severely if the channel decoder produces residual bit errors, e.g., due to heavy burst errors on the channel. A novel combined speech extrapolation and error detection algorithm is presented which can improve the speech significantly in the case of residual bit errors. This algorithm, which is part of the speech decoding process, uses a posteriori probabilities of speech parameters. With the extracted a posteriori probability, optimum estimators adapted to human perception can be applied and soft decision information can be exploited fully. In terms of perceptual performance, the MS (mean-square) estimator is superior to the MAP (maximum a posteriori) estimator. The method was tested under realistic conditions using an 8-kbit/s CELP (code excited linear prediction) codec. A significant improvement of subjective speech quality can be achieved.<>