关键词: 关键词识别, 混淆网络, 查询扩展, 音节相似度

Abstract: 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.

Key words: keyword recognition, confusion network, query expansion, syllable similarity