Maximally Informative Observables and Categorical Perception
Elaine Tsiang

TL;DR
This paper proposes a theoretical framework for perception based on information theory, introducing the concept of maximally informative observables as a foundation for understanding categorical perception and its implications for speech perception.
Contribution
It formulates perception within an information-theoretic framework and introduces maximally informative observables as a new theoretical basis for perception.
Findings
Categorical perception is linked to the existence of maximally informative observables.
Maximally informative observables can serve as a basis for a general theory of perception.
Implications for speech perception are discussed.
Abstract
We formulate the problem of perception in the framework of information theory, and prove that categorical perception is equivalent to the existence of an observable that has the maximum possible information on the target of perception. We call such an observable maximally informative. Regardless whether categorical perception is real, maximally informative observables can form the basis of a theory of perception. We conclude with the implications of such a theory for the problem of speech perception.
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Taxonomy
TopicsNeural Networks and Applications · Blind Source Separation Techniques · Visual perception and processing mechanisms
