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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...7 Hits 1 – 20 of 134 1 Learning Stress Patterns with a Sequence-to-Sequence Neural Network Prickett, Brandon; Pater, Joe In: Proceedings of the Society for Computation in Linguistics (2022) BASE Show details 2 Learning Repetition, but not Syllable Reversal Moreton, Elliott; Prickett, Brandon; Pertsova, Katya... In: Proceedings of the Annual Meetings on Phonology; Proceedings of the 2020 Annual Meeting on Phonology ; 2377-3324 (2021) BASE Show details 3 Learning syntacti parameter settings without triggers by assigning credit and blame Prickett, Brandon; Holladay, Kaden; Hucklebridge, Shay... In: CLS 55, 2019 : proceedings of the fifty-fifth annual meeting of the Chicago Linguistic Society (2020), S. 337-350 Leibniz-Zentrum Allgemeine Sprachwissenschaft Show details 4 French schwa and gradient cumulativity Smith, Brian W.; Pater, Joe In: Glossa: a journal of general linguistics; Vol 5, No 1 (2020); 24 ; 2397-1835 (2020) BASE Show details 5 Assimilation triggers metathesis in Balantak: Implications for theories of possible repair in Optimality Theory Pater, Joe In: University of Massachusetts Occasional Papers in Linguistics (2020) BASE Show details 6 *NC Pater, Joe In: North East Linguistics Society (2020) BASE Show details 7 French schwa and gradient cumulativity Smith, Brian W.; Pater, Joe In: Joe Pater (2019) BASE Show details 8 Learning Reduplication with a Neural Network without Explicit Variables Prickett, Brandon; Traylor, Aaron; Pater, Joe In: Joe Pater (2019) BASE Show details 9 Phonological typology in Optimality Theory and Formal Language Theory: Goals and future directions Pater, Joe In: Joe Pater (2019) BASE Show details 10 Learning syntactic parameters without triggers by assigning credit and blame Prickett, Brandon; Holladay, Kaden; Hucklebridge, Shay... In: Joe Pater (2019) BASE Show details 11 Generative linguistics and neural networks at 60: foundation, friction, and fusion Pater, Joe In: Joe Pater (2019) BASE Show details 12 Preface: SCiL 2019 Editors’ Note Jarosz, Gaja; Nelson, Max; O'Connor, Brendan... In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details 13 Substance matters: A reply to Jardine 2016 Pater, Joe In: Joe Pater (2018) BASE Show details 14 Seq2Seq Models with Dropout can Learn Generalizable Reduplication Prickett, Brandon; Traylor, Aaron; Pater, Joe In: Joe Pater (2018) BASE Show details 15 Preface: SCiL 2018 Editors’ Note Jarosz, Gaja; O'Connor, Brendan; Pater, Joe In: Proceedings of the Society for Computation in Linguistics (2018) BASE Show details 16 Learning opacity in Stratal Maximum Entropy Grammar ... Nazarov, Aleksei; Pater, Joe. - : arXiv, 2017 BASE Show details 17 The Oxford handbook of developmental linguistics Lidz, Jeffrey (Herausgeber); Snyder, William (Herausgeber); Pater, Joe (Herausgeber). - Oxford : Oxford University Press, 2016 UB Frankfurt Linguistik Show details 18 The Oxford handbook of developmental linguistics Lidz, Jeffrey; Snyder, William; Pater, Joe. - Oxford : Oxford University Press, 2016 MPI für Psycholinguistik Show details 19 Harmonic grammar and harmonic serialism McCarthy, John J. (Herausgeber); Pater, Joe (Herausgeber). - Bristol, CT : Equinox Publishing, 2016 BLLDB UB Frankfurt Linguistik Show details 20 Gradient Exceptionality in Maximum Entropy Grammar with Lexically Specific Constraints Moore-Cantwell, Claire; Pater, Joe. - 2016 Abstract: The number of exceptions to a phonological generalization appears to gradiently affect its productivity. Generalizations with relatively few exceptions are relatively productive, as measured in tendencies to regularization, as well as in nonce word productions and other psycholinguistic tasks. Gradient productivity has been previously modeled with probabilistic grammars, including Maximum Entropy Grammar, but they often fail to capture the fixed pronunciations of the existing words in a language, as opposed to nonce words. Lexically specific constraints allow existing words to be produced faithfully, while permitting variation in novel words that are not subject to those constraints. When each word has its own lexically specific version of a constraint, an inverse correlation between the number of exceptions and the degree of productivity is straightforwardly predicted. ; El nombre d'excepcions a una generalització fonològica sembla que afecta de forma gradual la seva productivitat. Les generalitzacions amb relativament poques excepcions són bastant productives, per les mesures en tendències a la regularització i per les produccions de mots sense sentit i altres tasques psicolingüístiques. La productivitat gradual s'ha modelat prèviament amb gramàtiques probabilístiques, incloent-hi la gramàtica de màxima entropia, però sovint no aconsegueixen recollir les pronunciacions fixes de paraules existents en una llengua, contràriament al que passa amb les paraules sense sentit. Les restriccions especificades lèxicament permeten produir els mots existents de manera fidel i al mateix temps permeten variació en mots nous, que no estan subjectes a aquestes restriccions. Quan cada mot té la seva pròpia versió d'una restricció especificada lèxicament es prediu directament una correlació inversa entre el nombre d'excepcions i el grau de productivitat. Keyword: Computational phonology; Excepcions; Exceptions; Fonologia computacional; Gramàtica de màxima entropia; Indexed constraints; Maximum entropy grammar; Restriccions indexades; Variació; Variation URL: https://ddd.uab.cat/record/166691 https://doi.org/10.5565/rev/catjl.183 BASE Hide details Page: 1 2 3 4 5...7

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