Robust multi-stream speech recognition based on weighting the output probabilities of feature components

Traditional multi-stream fusion methods in speech recognition try to control the stream influences on the decision by weighting the stream outputs. This paper proposes a new stream fusion method which weights not only the stream outputs, but also the output probabilities of feature components. The effect of the new fusion method on stream influences on the decision is discussed and two stream fusion schemes based on the mariginalisation and soft decision models in missing data techniques are also proposed. Experimental results on hybrid sub-band speech recognizer show that the proposed approaches can adjust the stream influences adaptively and outperform the traditional multi-stream methods in various noisy environments.