This course aims to examine the current state and future prospects of affect in computing and cognition. The objective is to provide knowledge in several aspects of affect: sensation, representation, expression and then show applications of this knowledge in human-computer-interaction. By the end of this course, students should have learned how emotions/affect can be quantified through behavioral/physiology measures and what are the current state-of-art applications in this newly emerging field.

An introduction to computational modeling in cognitive science, including computer simulation models of complex cognition, models within artificial intelligence, models based on neural mechanisms and networks, and formal and mathematical models in areas such as psychology, linguistics, and philosophy. Mathematical and computational modeling of the evolution of cognition. Models of cognition that extend beyond the boundaries of the person to include the environment, artifacts, social interactions, and culture.

Course Content: Lecture PresentationsHomework and Projects

Suitable for graduate students interested in doing theoretical or applied (computational, ELT, etc.) linguistic research using corpora.

The study of language using corpora. Usage of corpora within linguistics and cognitive science. Definition and varieties of corpora. Building a corpus: sampling, representativeness, encoding and annotation. Characteristics of major available corpora. Necessary statistics to interpret corpus data. Using corpora: corpora in psycholinguistics, corpora and syntax, semantics, and discourse; statistical natural language processing. Using (or writing tools) for corpus-based language studies. Conducting a research project on available corpora.

Course content: PresentationsExams