A new two-stage keyword spotting system was proposed based on syllable graph for audio information retrieval task

which could efficiently spot the interesting words in mass speech data

thus serve for the national security.It comprised two stages – preprocessing and searching.In the preprocessing stage

the audio data was recognized into syllable graph which included high accuracy syllable candidates

and unsupervised MLLR（maximum likelihood linear regression） adaptation was carried out iteratively to further improve the accuracy of the syllable graph.In the searching stage

to answer the frequent queries from users

searching for matched keywords was only scanned in the graph for likely syllable strings.A forward-backward algorithm based on syllable N-grammar was used to calculate confidence measures for further filtering of the searching result.Experimental results show the system achieved good performances in both recall rate and accuracy rate

and in the searching stage only 0.01 times of real time is needed

which can meet the demand for fast retrieval.