After taking this course, the students will be able to
- describe, characterize and compare probabilistic and structural frameworks for representing language;
- characterize and discuss the relationship between the language representation frameworks and the cognitive processes involved in various aspects of language acquisition (such as word learning or speech segmentation);
- evaluate and analyze computational models of language learning.
Research masters students who take this course are expected to follow the lectures of the course \"Cognitive Models of Language Learning\". The final evaluation will be based on a research project, the topic of which will be determined after meeting with the instructor.
We will discuss using formal models for studying human language learning. In the first part of the course, we will focus on the high-level objectives of studying human language, the general properties of computational models of language learning, and the most common frameworks for developing them. In the second half of the coursewe will focus on the cognitive processes involved in human language acquisition including speech segmentation, the association of words to meanings, learning language structure, and formation of linguistic categories, and analyze a number of computational models of each of these aspects.