Capturing perceptual expertise: a sound equalization expert system

摘要

This paper describes an intelligent interface to assist in the expert perceptual task of sound equalization. Inductive learning is used to acquire expert skill using nearest neighbor pattern recognition. This skill is then used in a sound equalization expert system, which proficiently adjusts the timbres (tonal qualities) of sound in a context-dependent fashion. The computer is used as a tool to sense, process, and act in helping the user perform a perceptual task. The developed system shows that the nearest-neighbor context-dependent equalization is rated 68% higher than the set linear average equalization and that it is preferred 81% of the time.