The A* speech recognition system on parallel architectures

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. In addition to the main CPU, almost every computer is equipped with a Graphics Processors Unit (GPU) which is in essence a specialized parallel processor. This paper explore how performance of speech recognition systems can be enhanced by using the A* algorithm which allows better parallelization over the Viterbi algorithm and a GPU for the acoustic computations in large vocabulary applications. 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 combined with GPU for acoustic computation led to a speed-up factor of 5.2 over its sequential counterpart and an improvement of 5% absolute of the accuracy over the sequential Viterbi search at real-time.