Using A* for the parallelization of speech recognition systems

The speed of modern processors has remained constant over the last few years but the integration capacity continues to follow Moore´s law and thus, to be scalable, applications must be parallelized. This paper presents results in using the A* search algorithm in a large vocabulary speech recognition parallel system. This algorithm allows better parallelization over the Viterbi algorithm. First experiments with a “unigram approximation” heuristic resulted in approximatively 8.7 times less states being explored compared to our classical Viterbi decoder. The multi-thread implementation of the A* decoder led to a speed-up factor of 3 over its sequential counterpart.