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Paper data
nonlinear speech processing with oscillatory neural networks for speaker segregation

Rouat Jean, UQAC & Univ. de Sherbrooke
Pichevar Ramin, Univ. du Québec à Chicoutimi

Page numbers in the proceedings:
Volume III pp 521-524

Non linear Speech Processing

Paper abstract
Nonlinear masking of space-time representations of speech is a universal technique for speech processing. In the present work we use an AM representation of cochlear filterbank signals in combination with a mask that is derived from a network of oscillatory neurons. The proposed approach does not need any training or learning and the mask takes into account the dependence between points from the auditory derived representation. A potential application is illustrated in the context of speaker segregation.

A PDF version is available here