Modeling the Repetition-Based Recovering of Acoustic and Visual Sources With Dendritic Neurons.

ABSTRACT: In natural auditory environments, acoustic signals originate from the temporal superimposition of different sound sources. The problem of inferring individual sources from ambiguous mixtures of sounds is known as blind source decomposition. Experiments on humans have demonstrated that the auditory system can identify sound sources as repeating patterns embedded in the acoustic input. Source repetition produces temporal regularities that can be detected and used for segregation. Specifically, listeners can identify sounds occurring more than once across different mixtures, but not sounds heard only in a single mixture. However, whether such a behavior can be computationally modeled has not yet been explored. Here, we propose a biologically inspired computational model to perform blind sourc

SUBMITTER: Dellaferrera G 

PROVIDER: S-EPMC9097820 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature