Computational models of human sentence comprehension help researchers reason about how grammar might actually be used in the understanding process. Taking a cognitivist approach, this article relates computational psycholinguistics to neighboring fields (such as linguistics), surveys important precedents, and catalogs open problems.
Article
Models of Human Sentence Comprehension in Computational Psycholinguistics
John Hale
Article
Computational Phonology
Jane Chandlee and Jeffrey Heinz
Computational phonology studies the nature of the computations necessary and sufficient for characterizing phonological knowledge. As a field it is informed by the theories of computation and phonology.
The computational nature of phonological knowledge is important because at a fundamental level it is about the psychological nature of memory as it pertains to phonological knowledge. Different types of phonological knowledge can be characterized as computational problems, and the solutions to these problems reveal their computational nature. In contrast to syntactic knowledge, there is clear evidence that phonological knowledge is computationally bounded to the so-called regular classes of sets and relations. These classes have multiple mathematical characterizations in terms of logic, automata, and algebra with significant implications for the nature of memory. In fact, there is evidence that phonological knowledge is bounded by particular subregular classes, with more restrictive logical, automata-theoretic, and algebraic characterizations, and thus by weaker models of memory.
