CS4317 Language Systems

This course introduces the computational aspects of processing human languages with attention to military text systems. Topics include lexicography, morphology, grammars, parsing, semantics, deep neural-network architectures, large language models, language generation, language translation, connecting to databases, AI agents and agentic workflows. Prerequisite: CS3021 or two courses in Python programming, and CS3310.

Prerequisite

Prerequisite: CS3021 or two courses in programming, and CS3310.

Lecture Hours

3

Lab Hours

2

Course Learning Outcomes

• Understand the key concepts and terms in computational natural-language processing, and apply them to particular problems.

• Create grammars for particular subsets of natural language.

• Apply semantic constraints between sense pairs of natural-language words.

• Understand how large language models are used for generative AI.

• Implement language systems using packages exploiting large language models.

• Set up retrieval-augmented generation from databases to support large language models.

• Evaluate needs for agentic workflow and understand its processing.

• Evaluate discourse issues in language processing, particularly those not handled well by large language models.

• Understand how speech-understanding systems work and analyze their issues.