Speech Enhancement based on Linear Prediction Error Signals and Spectral Subtraction

Speech processing and recognition are key technologies to produce smart user interfaces in an increasing number of devices. Moreover, robust speech recognition is considered mandatory for a reliable operation of such elements in realistic working conditions. Through this paper, a method of processing speech degraded by noise and reverberation is proposed. This approach involves analyzing the prediction error signals from the Gradient Adaptive Lattice algorithm in order to produce a valid estimator suitable for being combined with Spectral Subtraction techniques. The paper includes an evaluation of the performance of the algorithm for several speech recognition experiments in a car environment.