A Biologically Motivated Solution to the Cocktail Party Problem Export

@article{citeulike:3782896, abstract = {We present a new approach to the cocktail party problem that uses a cortronic artificial neural network architecture (Hecht-Nielsen, 1998) as the front end of a speech processing system. Our approach is novel in three important respects. First, our method assumes and exploits detailed knowledge of the signals we wish to attend to in the cocktail party environment. Second, our goal is to provide preprocessing in advance of a pattern recognition system rather than to separate one or more of the mixed sources explicitly. Third, the neural network model we employ is more biologically feasible than are most other approaches to the cocktail party problem. Although the focus here is on the cocktail party problem, the method presented in this study can be applied to other areas of information processing.}, author = {Sagi, Brian and Nemat-Nasser, Syrus C. and Kerr, Rex and Hayek, Raja and Downing, Christopher and Hecht-Nielsen, Robert}, citeulike-article-id = {3782896}, citeulike-linkout-0 = {http://neco.mitpress.org/cgi/content/abstract/13/7/1575}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/11440598}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=11440598}, day = {1}, journal = {Neural Comp.}, keywords = {biological-inspired-modeling, neuro-coding, neuroethology}, month = {July}, number = {7}, pages = {1575--1602}, posted-at = {2008-12-12 17:00:32}, priority = {2}, title = {A Biologically Motivated Solution to the Cocktail Party Problem}, url = {http://neco.mitpress.org/cgi/content/abstract/13/7/1575}, volume = {13}, year = {2001} }

TY - JOUR ID - citeulike:3782896 L3 - citeulike-article-id:3782896 N2 - We present a new approach to the cocktail party problem that uses a cortronic artificial neural network architecture (Hecht-Nielsen, 1998) as the front end of a speech processing system. Our approach is novel in three important respects. First, our method assumes and exploits detailed knowledge of the signals we wish to attend to in the cocktail party environment. Second, our goal is to provide preprocessing in advance of a pattern recognition system rather than to separate one or more of the mixed sources explicitly. Third, the neural network model we employ is more biologically feasible than are most other approaches to the cocktail party problem. Although the focus here is on the cocktail party problem, the method presented in this study can be applied to other areas of information processing. IS - 7 JF - Neural Comp. EP - 1602 TI - A Biologically Motivated Solution to the Cocktail Party Problem VL - 13 SP - 1575 KW - biological-inspired-modeling KW - neuro-coding KW - neuroethology AU - Sagi, Brian AU - Nemat-Nasser, Syrus AU - Kerr, Rex AU - Hayek, Raja AU - Downing, Christopher AU - Hecht-Nielsen, Robert PY - 2001/07/01/ UR - http://neco.mitpress.org/cgi/content/abstract/13/7/1575 ER -