Paper: iROVER: Improving System Combination with Classification

ACL ID N07-2017
Title iROVER: Improving System Combination with Classification
Venue Human Language Technologies
Session Short Paper
Year 2007
Authors

We present an improved system combination technique, ˙ıROVER. Our approach obtains sig- nificant improvements over ROVER, and is consistently better across varying numbers of component systems. A classifier is trained on features from the system lattices, and selects the final word hypothesis by learning cues to choose the system that is most likely to be correct at each word location. This approach achieves the best result published to date on the TC-STAR 2006 English speech recognition evaluation set.