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PPM-Decay: A computational model of auditory prediction with memory decay.
Harrison, Peter M C; Bianco, Roberta; Chait, Maria; Pearce, Marcus T.
Afiliación
  • Harrison PMC; Computational Auditory Perception Research Group, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany.
  • Bianco R; Cognitive Science Research Group, Queen Mary University of London, London, UK.
  • Chait M; UCL Ear Institute, University College London, London, UK.
  • Pearce MT; UCL Ear Institute, University College London, London, UK.
PLoS Comput Biol ; 16(11): e1008304, 2020 11.
Article en En | MEDLINE | ID: mdl-33147209
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 pattern detection experiment-we show how this decay kernel improves the model's predictive performance for sequences whose underlying statistics change over time, and enables the model to capture effects of memory constraints on auditory pattern detection. The resulting model is available in our new open-source R package, ppm (https://github.com/pmcharrison/ppm).
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Percepción Auditiva / Simulación por Computador / Memoria Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Percepción Auditiva / Simulación por Computador / Memoria Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Estados Unidos