Speeding Up Dynamic Search Methods
in Speech Recognition

In speech recognition huge hypothesis spaces are generated. To overcome this problem dynamic programming can be used. In this paper we examine ways of speeding up this search process even more using heuristic search methods, multi-pass search and aggregation operators. The tests showed that these techniques can be applied together, and their combination could significantly speed up the recognition process. The run-times we obtained were 22 times faster than the basic dynamic search method, and 8 times faster than the multi-stack decoding method.