Dual Particle-Number RBPF for Speech Enhancement
Seyed Farid Mousavipour, Saeed Seyedtabaii
Journal of E-Technology, Vol. 2, No. 4, 2011.
DOI: 
Link: IPOMS: an Internet Public Opinion Monitoring System  Jie Ding, Jungang Xu
Abstract:
In this paper, performance of a dual particle-number Rao-Blackwellized particle filter (RBPF) for speech enhancement is evaluated. Speech is corrupted by additive white, colored and real industrial noises that degrade its intelligibility. The performance indexes are: Quality of the processed speech scored by PESQ and computation time. The simulation results indicate that the RBPF methods outperform some well known Kalman based algorithms in the cost of more computation time. The weakness, then, is overcome by the dual particle-number RBPF that saves the quality of the processed speech while reduces remarkably the computation time.