[CL+NLP Lunch] CL+NLP Lunch, Dan Garrette, April 10 @noon

[Dani Yogatama]

*CL+NLP Lunch *(*http://www.cs.cmu.edu/~nlp-lunch/
<http://www.cs.cmu.edu/~nlp-lunch/>*)
*Speaker*: Dan Garrette, The University of Texas at Austin
*Date*: Thursday, April 10, 2013
*Time*: 12:00 noon
*Venue*: GHC 6501

*Title*: Unsupervised learning of non+concatenative morphology

*Abstract*:
Grammar learning is a well-studied problem in NLP, but the task is
particularly difficult for low-resource languages.  In this talk, I
will discuss our current work in learning combinatory categorial
grammars from various forms of weak supervision.  First, I will show
how we can learn good sequence-based CCG supertaggers by encoding
universal, inherent properties of the CCG formalism as priors over
both the appearance of supertags and the transitions between
supertags.  These universal priors can, in turn, be combined with
corpus-specific knowledge derived from available (partial) tag
dictionaries and unannotated text to further improve tagging
performance.  Then, I will discuss our current efforts to extend these
principles to tree grammars to learn CCG parsers.  Finally, I will
discuss how simple annotations --- particularly those given in the
Graph Fragment Language developed at CMU --- may be used to help
learn parsers under extremely tight annotation budgets.

This work is in collaboration with Jason Baldridge, Chris Dyer, and Noah
Smith.

*Biography*:
Dan is a a Computer Science Ph.D. student at The University of Texas
at Austin. His research focuses on Natural Language Processing and
Machine Learning.  He was a Best Talk Award nominee at NAACL this
past year. He thinks slides should have less text and more animations.
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