An algorithm for learning phonological classes from distributional similarity
نویسندگان
چکیده
منابع مشابه
Phonological generalization from distributional evidence
We propose a model of L2 phonological learning in which the acquisition of novel phonological category inventories proceeds not by mapping L2 inputs onto existing category inventories available in L1 and other already known languages, but rather through general categorization processes in which L1 and other language knowledge serves as an inductive bias. This approach views linguistic knowledge...
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1 Introduction Phonological representations are typically thought of as abstract: for example, phonemes are argued to be comprised of abstract subphonemic units of some sort, whether distinctive features (e.g., Chomsky & Halle 1968), articulatory gestures (e.g., Browman & Goldstein 1989), or acoustic-phonetic dimensions (e.g., Pierre-humbert 2000). There is direct evidence that people are sensi...
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Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony (Peperkamp, Le Calvez, Nadal, & Dupoux, 2006). This ...
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Lexical-semantic resources, including thesauri and WORDNET, have been successfully incorporated into a wide range of applications in Natural Language Processing. However they are very difficult and expensive to create and maintain, and their usefulness has been severely hampered by their limited coverage, bias and inconsistency. Automated and semi-automated methods for developing such resources...
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Distributional similarity is a classic technique for entity set expansion, where the system is given a set of seed entities of a particular class, and is asked to expand the set using a corpus to obtain more entities of the same class as represented by the seeds. This paper shows that a machine learning model called positive and unlabeled learning (PU learning) can model the set expansion probl...
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ژورنال
عنوان ژورنال: Phonology
سال: 2020
ISSN: 0952-6757,1469-8188
DOI: 10.1017/s0952675720000056