Efficient keyword spotting system for information retrieval - LUO Jun; OU Zhi-jian (Tongxin xuebao)
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.