Time+Place: Tuesday 24/02/2015 14:30 Room 337-8 Taub Bld.
Title: Situated Learning and Understanding of Natural Language
Speaker: Yoav Artzi - CS-Lecture http://yoavartzi.com/
Affiliation: Computer Science & Engineering dept., University of Washington
Host: Irad Yavneh

Abstract:


Robust language understanding systems have the potential to transform 
how we interact with computers. However, significant challenges in 
automated reasoning and learning remain to be solved before we achieve 
this goal. To accurately interpret user utterances, for example when 
instructing a robot, a system must jointly reason about word meaning, 
grammatical structure, conversation history and world state. 
Additionally, to learn without prohibitive data annotation costs, 
systems must automatically make use of weak, situated linguistic cues 
for autonomous language learning.

In this talk, I will present a framework that uses situated interactions 
to learn to map sentences to rich, logical meaning representations. The 
approach jointly induces the structure of a complex natural language 
grammar and estimates its parameters, while relying on various learning 
cues, such as easily gathered demonstrations and even raw conversations 
without any additional annotation effort. It achieves state-of-the-art 
performance on a number of tasks, including robotic interpretation of 
navigational directions and learning to understand user utterances in 
dialog systems. Such an approach, when integrated into complete systems, 
has the potential to achieve continuous, autonomous learning by 
participating in actual interactions with users.


Short Bio:

Yoav Artzi is a Ph.D. candidate in the Computer Science & Engineering 
department at the University of Washington, Seattle. His research 
interests are in the intersection of natural language processing and 
machine learning. In particular, he focuses on designing latent variable 
learning algorithms that recover rich representations of linguistic 
meaning for situated natural language understanding. He completed a 
B.Sc. summa cum laude in Computer Science in Tel Aviv University, and is 
a recipient of the 2014 Microsoft Research PhD Fellowship and the 2012 
Yahoo Key Scientific Challenge award.