The speed of modern processors has remained constant over the last few years 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 explores how performances of speech recognition systems can be enhanced by using GPU for the acoustic computations and multi-core CPUs for the Viterbi search in a large vocabulary application. The multi-core implementation of our speech recognition system runs 1.3 times faster than the single-threaded CPU implementation. Addition of the GPU for dedicated acoustic computations increases the speed by a factor of 2.8, leading to a word accuracy improvement of 16.6% absolute at real-time, compared to the single-threaded CPU implementation.
Bibliographic reference. Cardinal, Patrick / Dumouchel, Pierre / Boulianne, Gilles (2009): "Using parallel architectures in speech recognition", In INTERSPEECH-2009, 3039-3042.