The Cambridge Handbook of Morphology 2016
DOI: 10.1017/9781139814720.003
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Cited by 9 publications
(13 citation statements)
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“…The connection between form and meaning can be dynamic and relational, allowing morphological theory to reframe its semiotic legacy. In fact, it has been argued that since its discriminative underpinnings emphasize that language is a system of différence , discriminative learning elegantly carries the discipline back to its Saussurean heritage (Blevins, 2016 ).…”
Section: Discussionmentioning
confidence: 99%
“…The connection between form and meaning can be dynamic and relational, allowing morphological theory to reframe its semiotic legacy. In fact, it has been argued that since its discriminative underpinnings emphasize that language is a system of différence , discriminative learning elegantly carries the discipline back to its Saussurean heritage (Blevins, 2016 ).…”
Section: Discussionmentioning
confidence: 99%
“…In this study, we challenge a computational implementation of Word and Paradigm Morphology (Blevins, 2016;Matthews & Matthews, 1972), the 'discriminative lexicon' (DL) (Baayen et al, 2019), with the task of modeling the noun system of Maltese, a Semitic language spoken in Europe. The DL model differs from most theories of morphology in that it defines mappings between form and meaning (comprehension) and meaning and form (production) without requiring theoretical constructs such as stems, exponents, and inflectional classes.…”
Section: Introductionmentioning
confidence: 99%
“…But what if the analysis of complex words into simpler parts proves to be difficult, and, if possible, rather arbitrary (Katamba 1978;Hockett 1954;Blevins 2016a)? In that case speakers could not work out the necessary rules or schemas, which then raises the question by what mechanisms speakers can comprehend and produce complex words.…”
Section: Introductionmentioning
confidence: 99%
“…The Discriminative Lexicon is a comprehensive theory of the mental lexicon Baayen et al (2018;2019b); Chuang et al (2020b;c; that brings together several strands from independent theories: With word and paradigm theory it shares the hypothesis that words, not morphemes, stems or exponents are the relevant cognitive units (Blevins 2006;2016a); 1 with distributional semantics it shares the hypothesis that words get their meaning in utterances (Firth 1957;Landauer & Dumais 1997;Sahlgren 2008;Weaver 1955); from error-driven learning it implements the hypothesis learning is the result of minimizing prediction errors (Rescorla & Wagner 1972;Widrow & Hoff 1960). 2 From machine learning it incorporates the insight that fully connected neural networks are very successful at language learning (Boersma et al 2020;Magnuson et al 2020;Malouf 2017;Pater 2019;Prickett et al 2018).…”
Section: Introductionmentioning
confidence: 99%
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