Application of the Bayesian probability network to music scene analysis
Kunio Kashino, Kazuhiro Nakadai, Tomoyoshi Kinoshita, Hidehiko Tanaka · 1998
We propose a process model for hierarchical perceptual sound organization, which recognizes perceptual sounds included in incoming sound signals. We consider perceptual sound organization as a scene analysis problem in the auditory domain. Our current application is a music scene analysis system, which recognizes rhythm, chords, and source-separated musical notes included in incoming music signals. Our process model consists of multiple processing modules and a probability network for information integration. The structure of our model is conceptually based on the blackboard architecture. However, employment of a Bayesian probability network has facilitated integration of multiple sources of information provided by autonomous modules without global control knowledge. 1 Introduction We humans recognize or understand existence, localization and movements of external entities through five senses. We call this function "scene analysis". Scene analysis is viewed here as an information pr...