Acceleration of spoken term detection using a suffix array by assigning optimal threshold values to sub-keywords

We previously proposed a fast spoken term detection method that uses a suffix array data structure for searching large-scale speech documents. The method reduces search time via techniques such as keyword division and iterative lengthening search. In this paper, we propose a statistical method of assigning different threshold values to sub-keywords to further accelerate search. Specifically, the method estimates the numbers of results for keyword searches and then reduces them by adjusting the threshold values assigned to subkeywords. We also investigate the theoretical condition that must be satisfied by these threshold values. Experiments show that the proposed search method is 10% to 30% faster than previous methods.