2009
DOI: 10.1016/j.jml.2009.07.006
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Learning to order words: A connectionist model of heavy NP shift and accessibility effects in Japanese and English

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Cited by 89 publications
(102 citation statements)
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“…Evidence from English, Portuguese and German suggests that children's acquisition of relative clauses may depend on patterns in main clause utterances, with relative clauses that maintain more word order and morphological features of main clauses generally being easier to learn both within and between languages (Brandt, Diessel & Tomasello, 2008;Kidd & Bavin, 2002;Kidd, Brandt, Lieven & Tomasello, 2007). These results are consistent with the model presented in Chang (2009), which suggests that representations across similar structures, like the English main clause and the short-before-long dative, are shared, and it is these shared representations, and the relative frequencies of these shared representation that bring about short-before-long preferences in English and long-before-short preferences in Japanese. These results suggest a number of different regularities across sentence types: surface-level sentence word order, morphology or event structure may contribute to the observed phenomenon of active and passive relative clause frequencies in a language mirroring those of main clause active and passive sentence frequencies.…”
Section: Implications For Lexical Syntactic and Event Knowledge In supporting
confidence: 86%
See 1 more Smart Citation
“…Evidence from English, Portuguese and German suggests that children's acquisition of relative clauses may depend on patterns in main clause utterances, with relative clauses that maintain more word order and morphological features of main clauses generally being easier to learn both within and between languages (Brandt, Diessel & Tomasello, 2008;Kidd & Bavin, 2002;Kidd, Brandt, Lieven & Tomasello, 2007). These results are consistent with the model presented in Chang (2009), which suggests that representations across similar structures, like the English main clause and the short-before-long dative, are shared, and it is these shared representations, and the relative frequencies of these shared representation that bring about short-before-long preferences in English and long-before-short preferences in Japanese. These results suggest a number of different regularities across sentence types: surface-level sentence word order, morphology or event structure may contribute to the observed phenomenon of active and passive relative clause frequencies in a language mirroring those of main clause active and passive sentence frequencies.…”
Section: Implications For Lexical Syntactic and Event Knowledge In supporting
confidence: 86%
“…For example, in language production, the frequencies with which verbs appear in alternative syntactic contexts has consequences for sentence production choices of sentences containing those verbs (Arnold, Wasow, Asudeh & Alrenga, 2004;Bernolet & Hartsuiker, 2010;Stallings et al, 1998) as do the distributional pairings between noun animacy and sentence structure (Bresnan & Ford, 2010;Reali & Christiansen, 2007;Gennari & MacDonald, 2009). Like comprehenders, language producers implicitly learn statistical patterns of their linguistic environment, and this information affects production choices and accuracy (Boyd & Goldberg, 2011;Chang, 2009;Dell, Reed, Adams & Meyer, 2000;Warker & Dell, 2006). Language users also have learned the statistics of their visual environment, with consequences for codability in picture description tasks, where, for example, recognition of a ball is influenced by recognition of a throwing action and vice versa (Almor et al, 2009;Handy et al, 2003;Knoeferle & Crocker, 2006;Palmer, 1975).…”
Section: Multiple Forces Shaping Production Choicesmentioning
confidence: 99%
“…Furthermore, its predictions about early structural biases in preferential looking, namely that causative-transitive mappings are learned earlier than non-causativeintransitive mappings, have been confirmed in several syntactic bootstrapping studies in different languages (Gertner & Fisher, 2012;Matsuo, Kita, Shinya, Wood, & Naigles, 2012;Noble, Rowland, & Pine, 2011). More broadly, the model provides a general account of language acquisition and sentence production, learning typologically-different languages such as English, Japanese, and German (Chang, 2009;Chang, Baumann, Pappert, & Fitz, 2014) and successfully models a range of findings from the child and adult production literature, for example structural priming, conceptual/lexical accessibility, heavy NP shift and the accessibility hierarchy (Chang, 2009;Chang et al, 2006;Fitz, Chang, & Christiansen, 2011;Rowland, Chang, Ambridge, Pine, & Lieven, 2012).…”
Section: A Connectionist Model Of Acquisition Of the English Locativementioning
confidence: 72%
“…Because lexical competition at the choice point can influence structural choice (Bock, 1982;Chang, 2009), the model had to relay information about its lexical choices back to the sequencing system. It did this by passing back the winning Produced Word output as the next Previous Word input.…”
Section: Model Architecturementioning
confidence: 99%
“…These two differences can be seen in the Japanese version of 'John gave the book to Mary', which would be 'John-ga Mary-ni book-o gave' (when expressed with English content words). Chang [2] trained the Dual-path model on either English or Japanese input, and the model was able to acquire both languages to a similar degree. More importantly, the model was able to explain cross-linguistic differences in production biases in the two languages.…”
Section: The Dual-path Modelmentioning
confidence: 99%