Speech enhancement based on nonlinear models using particle filters

IEEE Transactions on Neural Networks

Volumn 20, Issue 12, 2009, Pages 1923-1937

  Mustiere, Frédéric ^a   Bolić, Miodrag ^a   Bouchard, Martin ^a  

^a UNIVERSITY OF OTTAWA   (Canada)

Author keywords

Nonlinear; Particle filters (PFs); Rao Blackwellized particle filter (RBPF); Speech denoising; Speech enhancement

Indexed keywords

COLORED NOISE; ENHANCEMENT ALGORITHMS; EXPERIMENTAL CONDITIONS; GLOBAL MODELS; IMPORTANCE FUNCTIONS; LINEAR MODEL; LOW SIGNAL-TO-NOISE RATIO; MULTIPLE NEURONS; NOISE REDUCTIONS; NOISE SIGNALS; NON-DUAL; NON-LINEAR MODEL; NON-LINEARITY; OBJECTIVE QUALITY MEASURES; PARTICLE FILTER; RAO-BLACKWELLIZATION; RAO-BLACKWELLIZED PARTICLE FILTER; RAO-BLACKWELLIZED PARTICLE FILTER (RBPF); SPEECH DENOISING; SPEECH MODELS; SPEECH PRODUCTION;

AIR FILTERS; ALGORITHMS; DISTRIBUTED COMPUTER SYSTEMS; MEASUREMENT THEORY; NEURONS; NONLINEAR FILTERING; SIGNAL TO NOISE RATIO; TARGET TRACKING;

SPEECH ENHANCEMENT;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; HUMAN; NOISE; NONLINEAR SYSTEM; PHYSIOLOGY; SIGNAL PROCESSING; SPEECH INTELLIGIBILITY;

ALGORITHMS; HUMANS; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); NOISE; NONLINEAR DYNAMICS; SIGNAL PROCESSING, COMPUTER-ASSISTED; SPEECH INTELLIGIBILITY;

EID: 72149097060     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2009.2033367     Document Type: Article

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