A model of lexical variation and the grammar with application to Tagalog nasal substitution

Dados Bibliográficos

ID11292243
AutoresKie Zuraw (0000-0001-5691-5646, University of California, Los Angeles, autor correspondente)
Ano2010
Volume28
Fascículo2
Páginas417-472
Data de publicação2010-05-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoNatural Language and Linguistic Theory (JOURNAL)
Identificadores do periódicoISSN: 0167-806X • E-ISSN: 1573-0859
EditoraSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s11049-010-9095-z
OpenAlexW2093787758
IdiomaEN
Citações recebidas41
Referências citadas44

This paper presents a case of patterned exceptionality. The case is Tagalog nasal substitution, a phenomenon in which a prefix-final nasal fuses with a stem-initial obstruent. The rule is variable on a word-by-word basis, but its distribution is phonologically patterned, as shown through dictionary and corpus data. Speakers appear to have implicit knowledge of the patterning, as shown through experimental data and loan adaptation. A grammar is proposed that reconciles the primacy of lexical information with regularities in the distribution of the rule. Morphologically complex words are allowed to have their own lexical entries, whose use is preferred to on-the-fly morphological concatenation. The grammar contains lower-ranked markedness constraints that govern the behavior of novel words. Faithfulness for lexicalized full words is ranked high, so that an established word will have a stable pronunciation. But when a word is newly coined through affixation, the outcome varies according the lexical trends. A crucial aspect of the proposal is that the ranking of the “subterranean” markedness constraints can be learned despite training data in which all words are pronounced faithfully, using Boersma’s (1997, 1998) Gradual learning algorithm. The paper also shows, by summarizing the rule’s behavior in related languages, that the same constraints, in different rankings, seem to be at work even in languages reported to lack variation

Grammar · Linguistics · Markedness · Natural language processing · Pronunciation · Computer Science · Linguistic Variation and Morphology · Natural Language Processing Techniques · Phonetics and Phonology Research · Artificial Intelligence