METHOD FOR ADAPTIVE ON-LINE DATA FUSION IN MULTI-CHANNEL AUTOMATIC SPEECH RECOGNITION SYSTEMS

摘要

In this paper describes a method for adaptive, parameter-independent, on-line channels' weight estimation, based on entropy in the output probabilities from ANN classifiers, rather than the noise level or SNR estimation. A recursive formula for channel combination calculation, based on approximation of all possible channels combination, is deduced. The proposed method has been used to develop multi-channel distributed speech recognition (DSR) system. From experiments a conclusion can be drawn that the use of proposed method result in absolute system accuracy improvement of 12.4% in comparison with the base one-channel DSR system from ETSI Aurora Project.