Application research of confusion network in spoken document retrieval system
Chengli Sun · Computer Engineering and Applications Journal · 2010
A syllable confusion network based spoken document content retrieval system is presented.A two-stage decoding based query automatic expansion method is proposed.It is achieved by first using a modified Viterbi decoder to calculate confusion syllable likehihood score in confusable syllable lattice,and then running A* search algorithm to generate mostly confusable phrases from lattice.The expansion terms are automaticly generated by its confidence score.Experimental results show that the proposed method can effectively improve term detection rate.