Abstract
This paper proposes novel heuristic algorithm called gravitational search algorithm (GSA) to speech enhancement. Stochastic and heuristic algorithms like particle swarm optimization (PSO) and some of its variants have been adapted to the field of speech enhancement in recent years. Although standard PSO (SPSO) finds good solutions, it suffers from the premature convergence by getting trapped into local optimum. In order to increase the diversity in search space and to improve the local searching capability, another recently developed heuristic algorithm GSA is proposed to speech enhancement in this paper. GSA is mainly constructed on the basis of law of gravity and the notion of mass interactions .The proposed algorithm is studied for real world noise condition called babble noise, at three different input SNR levels. To the best of our knowledge, there is no analysis about the intelligibility of enhanced speech using optimization techniques. In the present study, the proposed algorithm is compared with the standard PSO (SPSO) algorithm for dual channel speech enhancement, and the intelligibility analysis is also reported. Simulation results indicate that GSA-based algorithm outperforms the particle swarm optimization in adaptive noise cancellation with an improved speech quality and intelligibility.
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Prajna, K., Rao, G.S.B., Reddy, K.V.V.S. et al. A new approach to dual channel speech enhancement based on gravitational search algorithm (GSA). Int J Speech Technol 17, 341–351 (2014). https://doi.org/10.1007/s10772-014-9232-x
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DOI: https://doi.org/10.1007/s10772-014-9232-x