AbstractThe concept of an output-driven map formally characterizes an intuitive notion about phonology: that disparities between the input and the output are introduced only to the extent necessary to satisfy restrictions on outputs. When all of the grammars definable in a phonological system are output-driven, the implied structure provides significant computational benefits to language learners. An output-driven map imposes significant structure on the space of possible inputs for words, which can allow a learner to efficiently learn a lexicon of phonological underlying forms despite the vast number of possible lexica, as well as contend with the challenges of map/lexicon interactions inherent in phonological learning. This article presents a learning algorithm that exploits the structure of output-driven maps, illustrated with a system of grammars based in Optimality Theory. The algorithm highlights the roles played by contrast and paradigmatic information in phonological learning.
SubjectsPhonology, Language research, Language acquisition, Grammar, Cognitive mapping, Vocabulary development, Linguistic theory, Learning processes, Linguistic input, Morphemes
RightsCopyright for scholarly resources published in RUcore is retained by the copyright holder. By virtue of its appearance in this open access medium, you are free to use this resource, with proper attribution, in educational and other non-commercial settings. Other uses, such as reproduction or republication, may require the permission of the copyright holder.