A novel approach to HMM-based speech recognition systems using particle swarm optimization
Mathematical and Computer Modelling: An International Journal
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In this paper, dynamic programming alignment is replaced by a particle swarm optimization (PSO) procedure in time warping problem. The basic PSO is a very slow process to be applied to speech recognition application. In order to achieve a higher performance, by inspiring of PSO optimization methodology, we introduced a PSO Inspired Algorithm (PTW) that will significantly increase the computational performance of time warping in alignments of long length massive data sets. As a main enhancement, in PTW a pruning strategy with an add-in controlling threshold is defined that causes a considerable reduction in recognition time, while maintaining the system accuracy comparing to DTW.