Sound event recognition through expectancy-based evaluation ofsignal-driven hypotheses

A recognition system for environmental sounds is presented. Signal-driven classification is performed by applying machine-learning techniques on features extracted from a cochleogram. These possibly unreliable classifications are improved by creating expectancies of sound events based on context information.