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Modeling perception with hierarchical prediction: Auditory segmentation with deep predictive coding locates candidate evoked potentials in EEG
2020
Zenodo
The human response to music combines low-level expectations that are driven by the perceptual characteristics of audio with high-level expectations from the context and the listener's expertise. This paper discusses surprisal based music representation learning with a hierarchical predictive neural network. In order to inspect the cognitive validity of the network's predictions along their time-scales, we use the network's prediction error to segment electroencephalograms (EEG) based on the
doi:10.5281/zenodo.4245495
fatcat:qhrdh5e7mzh75cnvffx3gayuiu