Two working assumptions of theoretical phonologists lead to models in which a formal grammar (of some type) generates an infinite set of possible words, from which the actual words are a haphazard selection. These are the assumptions of awareness and compositionality. Awareness: Well-formedness judgments by native speakers reflect actual well-formedness. Compositionality: A well-formed whole is a well-formed combination of well-formed parts.
This talk will show that thorough application of these assumptions to large-scale data sets leads to models which look completely different from classical models. Considering both internal evidence and systematic data on judged well-formedness it will argue that the probabilistic generalizations over the lexicon characterizes the set of possible words in a way which is both simpler and more accurate than symbolic grammars. In addition, it will identify specific formal parallels between phonological well-formedness and processing which suggest that the two are intimately related.
For the colloquium series schedule, see the UMD Computational Linguistics Colloquium Series web page at http://umiacs.umd.edu/~resnik/cl_colloquium/. If you are interested in meeting with the speaker, please contact Mari Broman Olsen (molsen@umiacs.umd.edu) or Philip Resnik (resnik@umiacs.umd.edu).