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Language & Information Brown Bag: Mats Rooth

February 25, 2015, 1:00 pm - 2:00 pm
Location Schmitt Hall - 204
Posted InCollege of Humanities and Social Sciences

Mats Rooth (Cornell University)

Title: Headed Span Theory in the Finite State Calculus

Abstract: Headed span theory in phonology is an account of the
phonological substance that represents an autosegment such as a nasality or ATR feature as a labeled interval in a line, rather than as a vertex in a graph.  The intervals (or spans) have distinguished head positions. Span theory is attractive in computational approaches to phonology that work with finite state sets of strings and finite state relations between strings,
because of the possibility of straightforward string encodings of the phonological representations. This talk takes up the problem of working out a detailed, computationally executable construction of span theory in a finite state calculus.  This includes a construction the constraint families of headed span theory as operators. For instance, the headed faithfulness
constraint FthHdSp(F,X) penalizes underlying segments with value X for the feature F which do not head an [F,X] span on the surface.  The family is represented as an operator that constructs a finite state relation that inserts violation marks from a feature and a value. The constraint is directly used in the finite state calculus to optimize a candidate set. At the end, I sketch a proposal for representing transparent segments in
harmony using embedded exception spans.

Bio:
Mats Rooth is a professor at Cornell University, in the departments of Linguistics and Computing & Information Science.  He does research in two areas: computational linguistics and natural language semantics. He
has worked extensively on mixed symbolic/probabilistic models of syntax and the lexicon, on contrastive intonation (what is called focus), and on related phenomena such as ellipsis and presupposition. In addition to these, he is currently working on finite state optimality theory and web harvesting of intonational data.

http://conf.ling.cornell.edu/mr249/