PPM-Decay: A computational model of auditory prediction with memory decay.

ABSTRACT: Statistical learning and probabilistic prediction are fundamental processes in auditory cognition. A prominent computational model of these processes is Prediction by Partial Matching (PPM), a variable-order Markov model that learns by internalizing n-grams from training sequences. However, PPM has limitations as a cognitive model: in particular, it has a perfect memory that weights all historic observations equally, which is inconsistent with memory capacity constraints and recency effects observed in human cognition. We address these limitations with PPM-Decay, a new variant of PPM that introduces a customizable memory decay kernel. In three studies-one with artificially generated sequences, one with chord sequences from Western music, and one with new behavioral data from an auditory pa

SUBMITTER: Harrison PMC 

PROVIDER: S-EPMC7668605 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature