Computational Models of Language (CoLa) Reading Group

Discussion board: http://colareadinggroup.blogspot.com/

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Topics of interest include:

• computational models of language learning/acquisition and language use
• computational learning theory
• principles underlying models of language learning, change, and use
• modeling information extraction from language by humans

Language learning/acquisition: Language is an amazingly complex system of knowledge that must be learned from noisy input. That very young children who don't have the cognitive sophistication to count to four can accomplish this task is no small wonder. That adults who have far more cognitive resources and learning strategies - not to mention knowledge of their native language - can't is perhaps even more striking. How is this possible?

Computational learning theory: This includes formal representations of learnability, with particular interest in connections to language acquisition by humans.

Principles underlying models of language learning and change: These include discussions of fundamental assumptions (e.g., analysis by synthesis), processes underlying linguistic development, the relationship between language acquisition and language change, and processes of linguistic evolution.

Modeling information extraction from language by humans: Humans have an amazing ability to extract all kinds of information from language text, including direct information such as content and indirect information such as sentiment, attitude, emotion, and intention. Since the only information available is the language, humans must be using linguistic cues to do so. What are these cues? Are there additional informative cues available, besides the ones humans naturally use? How good (or bad) are humans at noticing various linguistic cues?