Towards improving the robustness of distributed speech recognition in packet loss

This work begins with an analysis into the effect of packet loss on the temporal components of the feature vector stream and its subsequent effect on recognition accuracy. Two methods of packet loss compensation are then compared. Reconstruction methods begin with interpolation and are extended to include prior statistical knowledge of the feature vector stream in the form of MAP estimation of lost vectors. Application of missing feature theory is also used to compensate for packet loss in the decoding phase of recognition. The feature vector is considered in terms of three temporal components, static, velocity and acceleration, and the reliability of these considered individually. Finally interleaving techniques are applied to reduce the perceived average burst lengths. Experimental results are then presented on the ETSI Aurora connected digit database.