Abstract
In this paper, the performance of two single channel speech enhancement filters: iterative Kalman and Rao-blackwellized particle filters, are evaluated. Speech intelligibility is deliberately deteriorated by adding white, colored and industrial noises. The quality of the processed speech is assessed by the Perceptual Quality of Speech (PESQ) index. Particular attention is also devoted to the reduction of the implementation cost, by assigning different model order and particle number to the voiced and unvoiced frames. The simulation results show mixed outcome. In some cases IKF and in some others RBPF gives better PESQ scores. The quality of each actually depends on the type of noise and input SNR. From viewpoint of computational costs, of course, IKF is more efficient than RBPF.
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