Computational model decodes speech by predicting it

UNIGE scientists developed a neuro-computer model which helps explain how the brain identifies syllables in natural speech. The model uses the equivalent of neuronal oscillations produced by brain activity to process the continuous sound flow of connected speech. The model functions according to a theory known as predictive coding, whereby the brain optimizes perception by constantly trying to predict the sensory signals based on candidate hypotheses (syllables in this model). More details

Towards an AI diagnosis like the doctor’s

Artificial intelligence is an important innovation in diagnostics, but the way these systems work is opaque. In a new article, researchers describe how they can make the AI show how it’s working, as well as let it diagnose more like a doctor, thus making AI more relevant to clinical practice. More details