|Abstract||We present a review on perception and cognition models designed for or applicable
to music. An emphasis is put on computational implementations.
We include findings from different disciplines: neuroscience, psychology, cognitive
science, artificial intelligence, and musicology. The article summarizes
the methodology that these disciplines use to approach the phenomena of music
understanding, the localization of musical processes in the brain, and the
flow of cognitive operations involved in turning physical signals into musical
symbols, going from the transducers to the memory systems of the brain. We
discuss formal models developed to emulate, explain and predict phenomena
involved in early auditory processing, pitch processing, grouping, source separation,
and music structure computation. We cover generic computational
architectures of attention, memory, and expectation that can be instantiated
and tuned to deal with specific musical phenomena. Criteria for the evaluation
of such models are presented and discussed. Thereby, we lay out the general
framework that provides the basis for the discussion of domain-specific music
models in a follow-up article [Purwins et al., 2008b].