Natural Language Understanding
Master in Artificial Intelligence Systems
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Description
Language is the fundamental means for humans to develop at the individual and social levels.
Natural Language Understanding (NLU) is the fundamental ability of artificial intelligence systems ( AIS ) to interact and talk to humans. AIS may be able to read and comprehend vast amounts of human language data ( speech, text, or multimedia ), and make sense of it. In the first part of the course, we will provide the students with basic knowledge about the natural language structure from the lexicon to the document-level formal models. Throughout the lectures and lab sessions, we will present and provide students with the knowledge and hands-on skills of the machine learning models ( symbolic and neural ) and their applications to natural language modeling and understanding.
Read the Story.
And here is an example of NLU parsing.
=======Lecture Topics, Slides, Lab============
Links below require UNITN credentials
Labs: You can find links to lab description and notebooks
in the "labmaterial" folder on didattica-online ( Sign in Required ).
Student-Lecturer communication: use the student-lecturer space on didattica-online ( Sign-in Required )
or the feedback form .
Lecture Presentations:
Course Description (Incl. Assignments and Grading)
Natural Language: from Spoken to Written Language
Language Modeling
Large Language Models: Benchmarks and Evaluation
Large Language Models: Architectures
Distributional Semantics and Word Vectors
Part-Of-Speech
Constituency and Dependency Grammars
Named Entities
Lexical Semantics
Sequence Labeling for NLU
Sequence Labeling for NLU with Neural Networks
Parsing Affective States: Sentiment Analysis
