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	<title>CiteULike: briordan's artificial-grammars</title>
	<description>CiteULike: briordan's artificial-grammars</description>


	<link>http://www.citeulike.org/user/briordan/tag/artificial-grammars</link>
	<dc:publisher>CiteULike.org</dc:publisher>
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	<dc:rights>Copyright &#169; 2004-2008 citeulike.org</dc:rights>
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<item rdf:about="http://www.citeulike.org/user/briordan/article/3019688">
    <title>Statistical Learning of Syntax: The Role of Transitional Probability</title>
    <link>http://www.citeulike.org/user/briordan/article/3019688</link>
    <description>&lt;i&gt;Language Learning and Development, Vol. 3, No. 1. (2007), pp. 1-42.&lt;/i&gt;</description>
    <dc:title>Statistical Learning of Syntax: The Role of Transitional Probability</dc:title>

    <dc:creator>Susan Thompson</dc:creator>
    <dc:creator>Elissa Newport</dc:creator>
    <dc:identifier>doi:10.1080/15475440709336999</dc:identifier>
    <dc:source>Language Learning and Development, Vol. 3, No. 1. (2007), pp. 1-42.</dc:source>
    <dc:date>2008-07-18T21:32:56-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Language Learning and Development</prism:publicationName>
    <prism:volume>3</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>1</prism:startingPage>
    <prism:endingPage>42</prism:endingPage>
    <prism:publisher>Psychology Press</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2939102">
    <title>Three Exemplars Allow at Least Some Linguistic Generalizations: Implications for Generalization Mechanisms and Constraints</title>
    <link>http://www.citeulike.org/user/briordan/article/2939102</link>
    <description>&lt;i&gt;Language Learning and Development, Vol. 4, No. 3. (2008), pp. 228-248.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The mechanism that allows learners to generalize over linguistic input and its relation to constraints on possible generalizations was explored in three experiments. Infants were familiarized briefly with words exhibiting stress patterns generated by a set of ordered principles, and then tested on new words that were either consistent or inconsistent with those principles. In Experiment 1, 9-month-olds generalized from three different heavy syllables (those ending in a consonant) heard during familiarization, to a new heavy syllable at test, but did not generalize from multiple tokens of one heavy syllable. Experiment 2 demonstrated that, although 9-month-olds were able to use three syllables to generalize the linguistically natural principle assigning stress to heavy syllables, they failed to use them to generalize a principle that does not occur in natural languages, suggesting that the mechanism requiring three input examples does not apply to all input equally. Experiment 3 demonstrated that although 9-month-olds failed to generalize the unnatural principle, 7.5-month-olds succeeded, suggesting that constraints on generalization can be acquired over development.</description>
    <dc:title>Three Exemplars Allow at Least Some Linguistic Generalizations: Implications for Generalization Mechanisms and Constraints</dc:title>

    <dc:creator>Louann Gerken</dc:creator>
    <dc:creator>Alex Bollt</dc:creator>
    <dc:identifier>doi:10.1080/15475440802143117</dc:identifier>
    <dc:source>Language Learning and Development, Vol. 4, No. 3. (2008), pp. 228-248.</dc:source>
    <dc:date>2008-06-28T11:51:02-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Language Learning and Development</prism:publicationName>
    <prism:volume>4</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>228</prism:startingPage>
    <prism:endingPage>248</prism:endingPage>
    <prism:publisher>Psychology Press</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2871219">
    <title>Statistical learning set: Emerging biases in the learning of an artificial grammar</title>
    <link>http://www.citeulike.org/user/briordan/article/2871219</link>
    <description>&lt;i&gt;(2007)&lt;/i&gt;</description>
    <dc:title>Statistical learning set: Emerging biases in the learning of an artificial grammar</dc:title>

    <dc:creator>Rick Dale</dc:creator>
    <dc:creator>Christopher Conway</dc:creator>
    <dc:source>(2007)</dc:source>
    <dc:date>2008-06-07T12:55:08-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2867458">
    <title>The Influence of Grammatical, Local, and Organizational Redundancy on Implicit Learning: An Analysis Using Information Theory</title>
    <link>http://www.citeulike.org/user/briordan/article/2867458</link>
    <description>&lt;i&gt;Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 31, No. 1. (January 2005), pp. 9-23.&lt;/i&gt;</description>
    <dc:title>The Influence of Grammatical, Local, and Organizational Redundancy on Implicit Learning: An Analysis Using Information Theory</dc:title>

    <dc:creator>Randall Jamieson</dc:creator>
    <dc:creator>DJK Mewhort</dc:creator>
    <dc:source>Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 31, No. 1. (January 2005), pp. 9-23.</dc:source>
    <dc:date>2008-06-05T17:53:58-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Journal of Experimental Psychology: Learning, Memory, and Cognition</prism:publicationName>
    <prism:volume>31</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>9</prism:startingPage>
    <prism:endingPage>23</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2859487">
    <title>Regularizing Unpredictable Variation: The Roles of Adult and Child Learners in Language Formation and Change</title>
    <link>http://www.citeulike.org/user/briordan/article/2859487</link>
    <description>&lt;i&gt;Language Learning and Development, Vol. 1, No. 2. (2005), pp. 151-195.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;In this article we investigate what learners acquire when their input contains inconsistent grammatical morphemes such as those present in pidgins and incipient creoles. In particular, we ask if learners acquire variability veridically or if they change it, making the language more regular as they learn it. In Experiment 1 we taught adult participants an artificial language containing unpredictable variation in 1 grammatical feature. We manipulated the amount of inconsistency and the meaning of the inconsistent item. Postexposure testing showed that participants learned the language, including the variable item, despite the presence of inconsistency. However, their use of variable items reflected their input. Participants exposed to consistent patterns produced consistent patterns, and participants exposed to inconsistency reproduced that inconsistency; they did not make the language more consistent. The meaning of the inconsistent item had no effect. In Experiment 2 we taught adults and 5- to 7-year-old children a similar artificial language. As in Experiment 1, the adults did not regularize the language. However, many children did regularize the language, imposing patterns that were not the same as their input. These results suggest that children and adults do not learn from variable input in the same way. Moreover, they suggest that children may play a unique and important role in creole formation by regularizing grammatical patterns.</description>
    <dc:title>Regularizing Unpredictable Variation: The Roles of Adult and Child Learners in Language Formation and Change</dc:title>

    <dc:creator>Carla Kam</dc:creator>
    <dc:creator>Elissa Newport</dc:creator>
    <dc:identifier>doi:10.1207/s15473341lld0102_3</dc:identifier>
    <dc:source>Language Learning and Development, Vol. 1, No. 2. (2005), pp. 151-195.</dc:source>
    <dc:date>2008-06-03T15:45:30-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Language Learning and Development</prism:publicationName>
    <prism:volume>1</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>151</prism:startingPage>
    <prism:endingPage>195</prism:endingPage>
    <prism:publisher>Psychology Press</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>general-language-acquisition</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2853824">
    <title>Principles of generalization for learning sequential structure in language</title>
    <link>http://www.citeulike.org/user/briordan/article/2853824</link>
    <description>&lt;i&gt;(2008)&lt;/i&gt;</description>
    <dc:title>Principles of generalization for learning sequential structure in language</dc:title>

    <dc:creator>Michael Frank</dc:creator>
    <dc:creator>D Ichinco</dc:creator>
    <dc:creator>Joshua Tenenbaum</dc:creator>
    <dc:source>(2008)</dc:source>
    <dc:date>2008-06-01T02:47:26-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>bayesian</prism:category>
    <prism:category>models</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2853822">
    <title>Information from multiple modalities helps five-month-olds learn abstract rules</title>
    <link>http://www.citeulike.org/user/briordan/article/2853822</link>
    <description>&lt;i&gt;Developmental Science (in press)&lt;/i&gt;</description>
    <dc:title>Information from multiple modalities helps five-month-olds learn abstract rules</dc:title>

    <dc:creator>Michael Frank</dc:creator>
    <dc:creator>JA Slemmer</dc:creator>
    <dc:creator>Gary Marcus</dc:creator>
    <dc:creator>Scott Johnson</dc:creator>
    <dc:source>Developmental Science (in press)</dc:source>
    <dc:date>2008-06-01T02:42:48-00:00</dc:date>
    <prism:publicationName>Developmental Science</prism:publicationName>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>multimodal-processing</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2844656">
    <title>Statistical learning in infants</title>
    <link>http://www.citeulike.org/user/briordan/article/2844656</link>
    <description>&lt;i&gt;Proceedings of the National Academy of Sciences, Vol. 99, No. 24. (26 November 2002), pp. 15250-15251.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;10.1073/pnas.262659399</description>
    <dc:title>Statistical learning in infants</dc:title>

    <dc:creator>Gerry Altmann</dc:creator>
    <dc:identifier>doi:10.1073/pnas.262659399</dc:identifier>
    <dc:source>Proceedings of the National Academy of Sciences, Vol. 99, No. 24. (26 November 2002), pp. 15250-15251.</dc:source>
    <dc:date>2008-05-29T14:38:38-00:00</dc:date>
    <prism:publicationYear>2002</prism:publicationYear>
    <prism:publicationName>Proceedings of the National Academy of Sciences</prism:publicationName>
    <prism:volume>99</prism:volume>
    <prism:number>24</prism:number>
    <prism:startingPage>15250</prism:startingPage>
    <prism:endingPage>15251</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>multimodal-processing</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>visual-world-paradigm</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2844648">
    <title>Modality independence of implicitly learned grammatical knowledge</title>
    <link>http://www.citeulike.org/user/briordan/article/2844648</link>
    <description>&lt;i&gt;Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 21, No. 4. (July 1995), pp. 899-912.&lt;/i&gt;</description>
    <dc:title>Modality independence of implicitly learned grammatical knowledge</dc:title>

    <dc:creator>Gerry Altmann</dc:creator>
    <dc:creator>Zoltán Dienes</dc:creator>
    <dc:creator>Alastair Goode</dc:creator>
    <dc:source>Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 21, No. 4. (July 1995), pp. 899-912.</dc:source>
    <dc:date>2008-05-29T14:34:53-00:00</dc:date>
    <prism:publicationYear>1995</prism:publicationYear>
    <prism:publicationName>Journal of Experimental Psychology: Learning, Memory, and Cognition</prism:publicationName>
    <prism:volume>21</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>899</prism:startingPage>
    <prism:endingPage>912</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>multimodal-processing</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2842724">
    <title>Systems of correlations in rule and category learning: Use of structured input in learning syntactic categories</title>
    <link>http://www.citeulike.org/user/briordan/article/2842724</link>
    <description>&lt;i&gt;Language and Cognitive Processes, Vol. 4, No. 2. (1989), pp. 127-155.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Three studies with artificial grammars investigated one property of natural language and one learning procedure which capitalises on this property to aid learning. Learning syntax is difficult because the rules and categories of syntax form a mutually defining system. Structural analogies to other systems (e.g. semantics, interaction) are limited and unreliable. On the other hand, treating syntax as a formal system and applying distributional analysis poses an extremely difficult learning problem. The property investigated is systematicity, coherence among multiple interpredictive features marking syntactic categories. The learning procedure is a method for directing attention to predictive features. This procedure predicts that an individual correlational rule or pattern will be learned more easily when it is part of a system of rules among intercorrelated features than when the identical rule occurs in isolationcomplexity facilitates learning. The artificial grammar experiments varied the structure of input; several versions of noun subcategories, analogous to gender or classifiers in natural languages, were used. They tested the prediction that learning an individual rule would be facilitated by other, intercorrelated rules. In all three experiments, the predicted benefit was found. These studies identify one way that the coherence in natural language might be used appropriately to guide and facilitate the learning process.</description>
    <dc:title>Systems of correlations in rule and category learning: Use of structured input in learning syntactic categories</dc:title>

    <dc:creator>Dorrit Billman</dc:creator>
    <dc:identifier>doi:10.1080/01690968908406360</dc:identifier>
    <dc:source>Language and Cognitive Processes, Vol. 4, No. 2. (1989), pp. 127-155.</dc:source>
    <dc:date>2008-05-28T20:37:07-00:00</dc:date>
    <prism:publicationYear>1989</prism:publicationYear>
    <prism:publicationName>Language and Cognitive Processes</prism:publicationName>
    <prism:volume>4</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>127</prism:startingPage>
    <prism:endingPage>155</prism:endingPage>
    <prism:publisher>Psychology Press</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/263741">
    <title>The time course of spoken word learning and recognition: studies with artificial lexicons.</title>
    <link>http://www.citeulike.org/user/briordan/article/263741</link>
    <description>&lt;i&gt;J Exp Psychol Gen, Vol. 132, No. 2. (June 2003), pp. 202-227.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The time course of spoken word recognition depends largely on the frequencies of a word and its competitors, or neighbors (similar-sounding words). However, variability in natural lexicons makes systematic analysis of frequency and neighbor similarity difficult. Artificial lexicons were used to achieve precise control over word frequency and phonological similarity. Eye tracking provided time course measures of lexical activation and competition (during spoken instructions to perform visually guided tasks) both during and after word learning, as a function of word frequency, neighbor type, and neighbor frequency. Apparent shifts from holistic to incremental competitor effects were observed in adults and neural network simulations, suggesting such shifts reflect general properties of learning rather than changes in the nature of lexical representations.</description>
    <dc:title>The time course of spoken word learning and recognition: studies with artificial lexicons.</dc:title>

    <dc:creator>JS Magnuson</dc:creator>
    <dc:creator>MK Tanenhaus</dc:creator>
    <dc:creator>RN Aslin</dc:creator>
    <dc:creator>D Dahan</dc:creator>
    <dc:source>J Exp Psychol Gen, Vol. 132, No. 2. (June 2003), pp. 202-227.</dc:source>
    <dc:date>2005-07-24T02:59:29-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:publicationName>J Exp Psychol Gen</prism:publicationName>
    <prism:issn>0096-3445</prism:issn>
    <prism:volume>132</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>202</prism:startingPage>
    <prism:endingPage>227</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>eye-movements</prism:category>
    <prism:category>spoken-word-recognition</prism:category>
    <prism:category>visual-world-paradigm</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2828473">
    <title>Statistical learning in infant language development</title>
    <link>http://www.citeulike.org/user/briordan/article/2828473</link>
    <description>&lt;i&gt;(2007), pp. 601-616.&lt;/i&gt;</description>
    <dc:title>Statistical learning in infant language development</dc:title>

    <dc:creator>Rebecca Gomez</dc:creator>
    <dc:source>(2007), pp. 601-616.</dc:source>
    <dc:date>2008-05-25T01:34:08-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:startingPage>601</prism:startingPage>
    <prism:endingPage>616</prism:endingPage>
    <prism:publisher>Oxford University Press</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2828438">
    <title>Modality-Constrained Statistical Learning of Tactile, Visual, and Auditory Sequences.</title>
    <link>http://www.citeulike.org/user/briordan/article/2828438</link>
    <description>&lt;i&gt;Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 31, No. 1. (January 2005), pp. 24-39.&lt;/i&gt;</description>
    <dc:title>Modality-Constrained Statistical Learning of Tactile, Visual, and Auditory Sequences.</dc:title>

    <dc:creator>Christopher Conway</dc:creator>
    <dc:creator>Morten Christiansen</dc:creator>
    <dc:source>Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 31, No. 1. (January 2005), pp. 24-39.</dc:source>
    <dc:date>2008-05-25T01:22:57-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Journal of Experimental Psychology: Learning, Memory, and Cognition</prism:publicationName>
    <prism:volume>31</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>24</prism:startingPage>
    <prism:endingPage>39</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2821771">
    <title>Visual Statistical Learning: Getting Some Help from the Auditory Modality</title>
    <link>http://www.citeulike.org/user/briordan/article/2821771</link>
    <description>&lt;i&gt;&lt;/i&gt;</description>
    <dc:title>Visual Statistical Learning: Getting Some Help from the Auditory Modality</dc:title>

    <dc:creator>Christopher Robinson</dc:creator>
    <dc:creator>Vladimir Sloutsky</dc:creator>
    <dc:date>2008-05-22T02:00:59-00:00</dc:date>
    <prism:publisher>Cognitive Science Society</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>multimodal-processing</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2796023">
    <title>Statistical approaches to language acquisition and the self-organizing consciousness: a reversal of perspective</title>
    <link>http://www.citeulike.org/user/briordan/article/2796023</link>
    <description>&lt;i&gt;Psychological Research, Vol. 69, No. 5. (1 June 2005), pp. 316-329.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Recent years have seen the upsurge of a new approach to language that moves away from the rule-based conventional framework. In this approach, mostly supported by the success of connectionist models, children learn language by exploiting the distributional properties of the input. It is argued in this paper that, in the same way as conforming to rules does not imply the existence of mental rules, conforming to statistical regularities does not imply that statistical computations are performed mentally. Sensitivity to statistical regularities can alternatively be conceived of as a by-product of the recurrent interplay between the properties of the current conscious content and the properties of the linguistic and extralinguistic environment. The validity of including the content of conscious experiences in an otherwise standard dynamical approach rooted in the notion of self-organization is discussed.</description>
    <dc:title>Statistical approaches to language acquisition and the self-organizing consciousness: a reversal of perspective</dc:title>

    <dc:creator>Pierre Perruchet</dc:creator>
    <dc:identifier>doi:10.1007/s00426-004-0205-6</dc:identifier>
    <dc:source>Psychological Research, Vol. 69, No. 5. (1 June 2005), pp. 316-329.</dc:source>
    <dc:date>2008-05-13T19:43:05-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Psychological Research</prism:publicationName>
    <prism:volume>69</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>316</prism:startingPage>
    <prism:endingPage>329</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>general-language-acquisition</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/844216">
    <title>Implicit learning and statistical learning: one phenomenon, two approaches</title>
    <link>http://www.citeulike.org/user/briordan/article/844216</link>
    <description>&lt;i&gt;Trends in Cognitive Sciences, Vol. 10, No. 5. (May 2006), pp. 233-238.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The domain-general learning mechanisms elicited in incidental learning situations are of potential interest in many research fields, including language acquisition, object knowledge formation and motor learning. They have been the focus of studies on implicit learning for nearly 40 years. Stemming from a different research tradition, studies on statistical learning carried out in the past 10 years after the seminal studies by Saffran and collaborators, appear to be closely related, and the similarity between the two approaches is strengthened further by their recent evolution. However, implicit learning and statistical learning research favor different interpretations, focusing on the formation of chunks and statistical computations, respectively. We examine these differing approaches and suggest that this divergence opens up a major theoretical challenge for future studies.</description>
    <dc:title>Implicit learning and statistical learning: one phenomenon, two approaches</dc:title>

    <dc:creator>Pierre Perruchet</dc:creator>
    <dc:creator>Sebastien Pacton</dc:creator>
    <dc:identifier>doi:10.1016/j.tics.2006.03.006</dc:identifier>
    <dc:source>Trends in Cognitive Sciences, Vol. 10, No. 5. (May 2006), pp. 233-238.</dc:source>
    <dc:date>2006-09-15T05:46:55-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Trends in Cognitive Sciences</prism:publicationName>
    <prism:volume>10</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>233</prism:startingPage>
    <prism:endingPage>238</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2784096">
    <title>The effect of functional morphemes on word segmentation in preverbal infants</title>
    <link>http://www.citeulike.org/user/briordan/article/2784096</link>
    <description>&lt;i&gt;Developmental Science, Vol. 11, No. 3. (May 2008), pp. 407-413.&lt;/i&gt;</description>
    <dc:title>The effect of functional morphemes on word segmentation in preverbal infants</dc:title>

    <dc:creator>Shi</dc:creator>
    <dc:creator>Rushen</dc:creator>
    <dc:creator>Lepage</dc:creator>
    <dc:creator>Melanie</dc:creator>
    <dc:identifier>doi:10.1111/j.1467-7687.2008.00685.x</dc:identifier>
    <dc:source>Developmental Science, Vol. 11, No. 3. (May 2008), pp. 407-413.</dc:source>
    <dc:date>2008-05-11T10:12:08-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Developmental Science</prism:publicationName>
    <prism:issn>1363-755X</prism:issn>
    <prism:volume>11</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>407</prism:startingPage>
    <prism:endingPage>413</prism:endingPage>
    <prism:publisher>Blackwell Publishing</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2773282">
    <title>Semantic reference and phrasal grouping in the acquisition of a miniature phrase structure language</title>
    <link>http://www.citeulike.org/user/briordan/article/2773282</link>
    <description>&lt;i&gt;Journal of Memory and Language, Vol. 25, No. 4. (August 1986), pp. 492-505.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;In this study we examine the roles of semantic reference and of grammatical morphology in the learning of an artificial syntax. Subjects assigned to one of three training conditions viewed sentences from a miniature phrase structure language. In the reference field condition, subjects saw sentences which each referred to an array of geometric figures. In the morphology condition no reference field was present, but inflectional suffixes marked each sentence's constituent structure. Control condition subjects studied sentences lacking semantic reference and inflectional morphology. Unlike control subjects, subjects in both the reference field and morphology conditions learned the miniature syntax, as evidenced by successful discrimination of novel grammatical versus ungrammatical sentences. Therefore, when surface features mark constituents, adult learning of complex syntactic regularities proceeds even in the absence of semantic reference.</description>
    <dc:title>Semantic reference and phrasal grouping in the acquisition of a miniature phrase structure language</dc:title>

    <dc:creator>Richard Meier</dc:creator>
    <dc:creator>Gordon Bower</dc:creator>
    <dc:identifier>doi:10.1016/0749-596X(86)90040-9</dc:identifier>
    <dc:source>Journal of Memory and Language, Vol. 25, No. 4. (August 1986), pp. 492-505.</dc:source>
    <dc:date>2008-05-08T17:24:11-00:00</dc:date>
    <prism:publicationYear>1986</prism:publicationYear>
    <prism:publicationName>Journal of Memory and Language</prism:publicationName>
    <prism:volume>25</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>492</prism:startingPage>
    <prism:endingPage>505</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2754297">
    <title>Grammaticality judgments in children: The role of age, working memory and phonological ability</title>
    <link>http://www.citeulike.org/user/briordan/article/2754297</link>
    <description>&lt;i&gt;Journal of Child Language, Vol. 35, No. 02. (2008), pp. 247-268.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;This paper examines the role of age, working memory span and phonological ability in the mastery of ten different grammatical constructions. Six- through eleven-year-old children (&#60;em&#62;n&#60;/em&#62;=68) and adults (&#60;em&#62;n&#60;/em&#62;=19) performed a grammaticality judgment task as well as tests of working memory capacity and receptive phonological ability. Children showed early mastery of some grammatical structures (e.g. word order, article omissions) while even the oldest children differed from adults on others (e.g. past tense, third person singular agreement). Working memory capacity and phonological ability accounted for variance in grammaticality judgments above and beyond age effects. In particular, working memory capacity correlated with structures involving verb morphology and word order; phonological ability was important for structures with low phonetic substance. Children's relative difficulty with the different constructions showed parallels to adult performance under memory load stress, indicating working memory capacity may be a limiting factor in their performance. Implications for performance by memory and phonologically impaired populations are discussed.</description>
    <dc:title>Grammaticality judgments in children: The role of age, working memory and phonological ability</dc:title>

    <dc:creator>Janet Mcdonald</dc:creator>
    <dc:source>Journal of Child Language, Vol. 35, No. 02. (2008), pp. 247-268.</dc:source>
    <dc:date>2008-05-04T17:34:27-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Journal of Child Language</prism:publicationName>
    <prism:volume>35</prism:volume>
    <prism:number>02</prism:number>
    <prism:startingPage>247</prism:startingPage>
    <prism:endingPage>268</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>grammatical-number</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
    <prism:category>syntactic-variation</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2696773">
    <title>Syntactic structure and artificial grammar learning: The learnability of embedded hierarchical structures</title>
    <link>http://www.citeulike.org/user/briordan/article/2696773</link>
    <description>&lt;i&gt;Cognition, Vol. 107, No. 2. (May 2008), pp. 763-774.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Embedded hierarchical structures, such as &#34;the rat the cat ate was brown&#34;, constitute a core generative property of a natural language theory. Several recent studies have reported learning of hierarchical embeddings in artificial grammar learning (AGL) tasks, and described the functional specificity of Broca's area for processing such structures. In two experiments, we investigated whether alternative strategies can explain the learning success in these studies. We trained participants on hierarchical sequences, and found no evidence for the learning of hierarchical embeddings in test situations identical to those from other studies in the literature. Instead, participants appeared to solve the task by exploiting surface distinctions between legal and illegal sequences, and applying strategies such as counting or repetition detection. We suggest alternative interpretations for the observed activation of Broca's area, in terms of the application of calculation rules or of a differential role of working memory. We claim that the learnability of hierarchical embeddings in AGL tasks remains to be demonstrated.</description>
    <dc:title>Syntactic structure and artificial grammar learning: The learnability of embedded hierarchical structures</dc:title>

    <dc:creator>Meinou de Vries</dc:creator>
    <dc:creator>Padraic Monaghan</dc:creator>
    <dc:creator>Stefan Knecht</dc:creator>
    <dc:creator>Pienie Zwitserlood</dc:creator>
    <dc:identifier>doi:10.1016/j.cognition.2007.09.002</dc:identifier>
    <dc:source>Cognition, Vol. 107, No. 2. (May 2008), pp. 763-774.</dc:source>
    <dc:date>2008-04-21T14:34:42-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Cognition</prism:publicationName>
    <prism:volume>107</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>763</prism:startingPage>
    <prism:endingPage>774</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2693734">
    <title>Grammatical pattern learning by human infants and cotton-top tamarin monkeys</title>
    <link>http://www.citeulike.org/user/briordan/article/2693734</link>
    <description>&lt;i&gt;Cognition, Vol. 107, No. 2. (May 2008), pp. 479-500.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;There is a surprising degree of overlapping structure evident across the languages of the world. One factor leading to cross-linguistic similarities may be constraints on human learning abilities. Linguistic structures that are easier for infants to learn should predominate in human languages. If correct, then (a) human infants should more readily acquire structures that are consistent with the form of natural language, whereas (b) non-human primates' patterns of learning should be less tightly linked to the structure of human languages. Prior experiments have not directly compared laboratory-based learning of grammatical structures by human infants and non-human primates, especially under comparable testing conditions and with similar materials. Five experiments with 12-month-old human infants and adult cotton-top tamarin monkeys addressed these predictions, employing comparable methods (familiarization-discrimination) and materials. Infants rapidly acquired complex grammatical structures by using statistically predictive patterns, failing to learn structures that lacked such patterns. In contrast, the tamarins only exploited predictive patterns when learning relatively simple grammatical structures. Infant learning abilities may serve both to facilitate natural language acquisition and to impose constraints on the structure of human languages.</description>
    <dc:title>Grammatical pattern learning by human infants and cotton-top tamarin monkeys</dc:title>

    <dc:creator>Jenny Saffran</dc:creator>
    <dc:creator>Marc Hauser</dc:creator>
    <dc:creator>Rebecca Seibel</dc:creator>
    <dc:creator>Joshua Kapfhamer</dc:creator>
    <dc:creator>Fritz Tsao</dc:creator>
    <dc:creator>Fiery Cushman</dc:creator>
    <dc:identifier>doi:10.1016/j.cognition.2007.10.010</dc:identifier>
    <dc:source>Cognition, Vol. 107, No. 2. (May 2008), pp. 479-500.</dc:source>
    <dc:date>2008-04-20T22:19:39-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Cognition</prism:publicationName>
    <prism:volume>107</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>479</prism:startingPage>
    <prism:endingPage>500</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2605823">
    <title>Rule Learning by Rats</title>
    <link>http://www.citeulike.org/user/briordan/article/2605823</link>
    <description>&lt;i&gt;Science, Vol. 319, No. 5871. (28 March 2008), pp. 1849-1851.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Using rules extracted from experience to solve problems in novel situations involves cognitions such as analogical reasoning and language learning and is considered a keystone of humans' unique abilities. Nonprimates, it has been argued, lack such rule transfer. We report that Rattus norvegicus can learn simple rules and apply them to new situations. Rats learned that sequences of stimuli consistent with a rule (such as XYX) were different from other sequences (such as XXY or YXX). When novel stimuli were used to construct sequences that did or did not obey the previously learned rule, rats transferred their learning. Therefore, rats, like humans, can transfer structural knowledge from sequential experiences. 10.1126/science.1151564</description>
    <dc:title>Rule Learning by Rats</dc:title>

    <dc:creator>Robin Murphy</dc:creator>
    <dc:creator>Esther Mondragon</dc:creator>
    <dc:creator>Victoria Murphy</dc:creator>
    <dc:identifier>doi:10.1126/science.1151564</dc:identifier>
    <dc:source>Science, Vol. 319, No. 5871. (28 March 2008), pp. 1849-1851.</dc:source>
    <dc:date>2008-03-28T11:03:44-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Science</prism:publicationName>
    <prism:volume>319</prism:volume>
    <prism:number>5871</prism:number>
    <prism:startingPage>1849</prism:startingPage>
    <prism:endingPage>1851</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2575207">
    <title>The effects of contextual constraints on spoken word recognition in an artificial lexicon</title>
    <link>http://www.citeulike.org/user/briordan/article/2575207</link>
    <description>&lt;i&gt;&lt;/i&gt;</description>
    <dc:title>The effects of contextual constraints on spoken word recognition in an artificial lexicon</dc:title>

    <dc:creator>Kathleen Pirog</dc:creator>
    <dc:creator>Richard Aslin</dc:creator>
    <dc:creator>Michael Tanenhaus</dc:creator>
    <dc:date>2008-03-23T17:37:02-00:00</dc:date>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>spoken-word-recognition</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>visual-world-paradigm</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2560642">
    <title>The Influence of Vowel Harmony on Turkish Native Speakers Learning an Artificial Language System</title>
    <link>http://www.citeulike.org/user/briordan/article/2560642</link>
    <description>&lt;i&gt;(2008)&lt;/i&gt;</description>
    <dc:title>The Influence of Vowel Harmony on Turkish Native Speakers Learning an Artificial Language System</dc:title>

    <dc:creator>Asli Altan</dc:creator>
    <dc:source>(2008)</dc:source>
    <dc:date>2008-03-19T13:23:02-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/1556925">
    <title>Syntax as a reflex: Neurophysiological evidence for early automaticity of grammatical processing</title>
    <link>http://www.citeulike.org/user/briordan/article/1556925</link>
    <description>&lt;i&gt;Brain and Language, Vol. In Press, Corrected Proof&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;It has been a matter of debate whether the specifically human capacity to process syntactic information draws on attentional resources or is automatic. To address this issue, we recorded neurophysiological indicators of syntactic processing to spoken sentences while subjects were distracted to different degrees from language processing. Subjects were either passively distracted, by watching a silent video film, or their attention was actively streamed away from the language input by performing a demanding acoustic signal detection task. An early index of syntactic violations, the syntactic Mismatch Negativity (sMMN), distinguished between grammatical and ungrammatical speech even under strongest distraction. The magnitude of the early sMMN (at &#60;150 ms) was unaffected by attention load of the distraction task. The independence of the early syntactic brain response of attentional distraction provides neurophysiological evidence for the automaticity of syntax and for its autonomy from other attention-demanding processes, including acoustic stimulus discrimination. The first attentional modulation of syntactic brain responses became manifest at a later stage, at ~200 ms, thus demonstrating the narrowness of the early time window of syntactic autonomy. We discuss these results in the light of modular and interactive theories of cognitive processing and draw inferences on the automaticity of both the cognitive MMN response and certain grammar processes in general.</description>
    <dc:title>Syntax as a reflex: Neurophysiological evidence for early automaticity of grammatical processing</dc:title>

    <dc:creator>Friedemann Pulvermuller</dc:creator>
    <dc:creator>Yury Shtyrov</dc:creator>
    <dc:creator>Anna Hasting</dc:creator>
    <dc:creator>Robert Carlyon</dc:creator>
    <dc:identifier>doi:10.1016/j.bandl.2007.05.002</dc:identifier>
    <dc:source>Brain and Language, Vol. In Press, Corrected Proof</dc:source>
    <dc:date>2007-08-13T06:24:21-00:00</dc:date>
    <prism:publicationName>Brain and Language</prism:publicationName>
    <prism:volume>In Press, Corrected Proof</prism:volume>
    <prism:category>aoa</prism:category>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>erps</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2428099">
    <title>AGL StimSelect: Software for automated selection of stimuli for artificial grammar learning</title>
    <link>http://www.citeulike.org/user/briordan/article/2428099</link>
    <description>&lt;i&gt;Behavior Research Methods, Vol. 40, No. 1. (February 2008), pp. 164-176.&lt;/i&gt;</description>
    <dc:title>AGL StimSelect: Software for automated selection of stimuli for artificial grammar learning</dc:title>

    <dc:creator>Bailey</dc:creator>
    <dc:creator>M Todd</dc:creator>
    <dc:creator>Pothos</dc:creator>
    <dc:creator>M Emmanuel</dc:creator>
    <dc:identifier>doi:10.3758/BRM.40.1.164</dc:identifier>
    <dc:source>Behavior Research Methods, Vol. 40, No. 1. (February 2008), pp. 164-176.</dc:source>
    <dc:date>2008-02-26T02:22:00-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Behavior Research Methods</prism:publicationName>
    <prism:issn>1554-351X</prism:issn>
    <prism:volume>40</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>164</prism:startingPage>
    <prism:endingPage>176</prism:endingPage>
    <prism:publisher>Psychonomic Society Publications</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>methods</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2438726">
    <title>Context repetition benefits are dependent on context redundancy</title>
    <link>http://www.citeulike.org/user/briordan/article/2438726</link>
    <description>&lt;i&gt;&lt;/i&gt;</description>
    <dc:title>Context repetition benefits are dependent on context redundancy</dc:title>

    <dc:creator>Gabriel Recchia</dc:creator>
    <dc:creator>Brendan Johns</dc:creator>
    <dc:creator>Michael Jones</dc:creator>
    <dc:date>2008-02-27T20:44:25-00:00</dc:date>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>contextual-diversity</prism:category>
    <prism:category>distributional-similarity</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2399450">
    <title>Native and Nonnative Speakers' Processing of a Miniature Version of Japanese as Revealed by ERPs</title>
    <link>http://www.citeulike.org/user/briordan/article/2399450</link>
    <description>&lt;i&gt;J. Cogn. Neurosci., Vol. 17, No. 8. (1 August 2005), pp. 1229-1244.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Several event-related potential (ERP) studies in second language (L2) processing have revealed a differential vulnerability of syntax-related ERP effects in contrast to purely semantic ERP effects. However, it is still debated to what extent a potential critical period for L2 acquisition, as opposed to the attained proficiency level in the L2, contributes to the pattern of results reported in previous ERP studies. We studied L2 processing within the model of a miniature version of a natural language, namely Japanese, specifically constructed to assure high proficiency of the learners. In an auditory ERP experiment, we investigated sentence processing of the &#34;Mini-Japanese&#34; in Japanese native speakers and German volunteers before and after training. By making use of three different types of violation, namely, word category, case, and classifier violations, native and nonnative ERP patterns were compared. The three types of violation elicited three characteristic ERP patterns in Japanese native speakers. The word category violation elicited an anteriorly focused, broadly distributed early negativity followed by a P600, whereas the case violation evoked a P600 which was preceded by an N400. The classifier violation led solely to a late left distributed negativity with an anterior focus. Although the P600 was similar for Japanese natives and learners, the N400 and the anterior negativities were not present in the learner group. The differences across groups suggest deviant neural processes in on-line syntactic and thematic processing in the L2 learners despite high behavioral skills.</description>
    <dc:title>Native and Nonnative Speakers' Processing of a Miniature Version of Japanese as Revealed by ERPs</dc:title>

    <dc:creator>Jutta Mueller</dc:creator>
    <dc:creator>Anja Hahne</dc:creator>
    <dc:creator>Yugo Fujii</dc:creator>
    <dc:creator>Angela Friederici</dc:creator>
    <dc:source>J. Cogn. Neurosci., Vol. 17, No. 8. (1 August 2005), pp. 1229-1244.</dc:source>
    <dc:date>2008-02-19T17:07:16-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>J. Cogn. Neurosci.</prism:publicationName>
    <prism:volume>17</prism:volume>
    <prism:number>8</prism:number>
    <prism:startingPage>1229</prism:startingPage>
    <prism:endingPage>1244</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>erps</prism:category>
    <prism:category>japanese</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2386532">
    <title>Different Neurophysiological Mechanisms Underlying Word and Rule Extraction from Speech</title>
    <link>http://www.citeulike.org/user/briordan/article/2386532</link>
    <description>&lt;i&gt;PLoS ONE, Vol. 2, No. 11. (2007)&lt;/i&gt;</description>
    <dc:title>Different Neurophysiological Mechanisms Underlying Word and Rule Extraction from Speech</dc:title>

    <dc:creator>Ruth Balaguer</dc:creator>
    <dc:creator>Juan Toro</dc:creator>
    <dc:creator>Antoni Rodriguez-Fornells</dc:creator>
    <dc:creator>Anne-Catherine Bachoud-Lévi</dc:creator>
    <dc:source>PLoS ONE, Vol. 2, No. 11. (2007)</dc:source>
    <dc:date>2008-02-15T15:07:24-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>PLoS ONE</prism:publicationName>
    <prism:volume>2</prism:volume>
    <prism:number>11</prism:number>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>erps</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2351492">
    <title>Implicit learning of second-, third-, and fourth-order adjacent and nonadjacent sequential dependencies</title>
    <link>http://www.citeulike.org/user/briordan/article/2351492</link>
    <description>&lt;i&gt;The Quarterly Journal of Experimental Psychology, Vol. 61, No. 3. (2008), pp. 400-424.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Serial reaction time (SRT) task studies have established that people can implicitly learn first- and second-order adjacent dependencies. Sequential confounds have made it impossible to draw conclusions regarding learning of nonadjacent dependencies and learning of third- and fourth-order adjacent dependencies. Addressing the confounds, the present study shows that people can implicitly learn second-, third-, and fourth-order adjacent and nonadjacent dependencies embedded in probabilistic sequences of target locations.</description>
    <dc:title>Implicit learning of second-, third-, and fourth-order adjacent and nonadjacent sequential dependencies</dc:title>

    <dc:creator>Gilbert Remillard</dc:creator>
    <dc:identifier>doi:10.1080/17470210701210999</dc:identifier>
    <dc:source>The Quarterly Journal of Experimental Psychology, Vol. 61, No. 3. (2008), pp. 400-424.</dc:source>
    <dc:date>2008-02-08T01:40:22-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>The Quarterly Journal of Experimental Psychology</prism:publicationName>
    <prism:volume>61</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>400</prism:startingPage>
    <prism:endingPage>424</prism:endingPage>
    <prism:publisher>Psychology Press</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2351451">
    <title>Finding Words and Rules in a Speech Stream: Functional Differences Between Vowels and Consonants</title>
    <link>http://www.citeulike.org/user/briordan/article/2351451</link>
    <description>&lt;i&gt;Psychological Science, Vol. 19, No. 2. (2008), pp. 137-144.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;ABSTRACT- We have proposed that consonants give cues primarily about the lexicon, whereas vowels carry cues about syntax. In a study supporting this hypothesis, we showed that when segmenting words from an artificial continuous stream, participants compute statistical relations over consonants, but not over vowels. In the study reported here, we tested the symmetrical hypothesis that when participants listen to words in a speech stream, they tend to exploit relations among vowels to extract generalizations, but tend to disregard the same relations among consonants. In our streams, participants could segment words on the basis of transitional probabilities in one tier and could extract a structural regularity in the other tier. Participants used consonants to extract words, but vowels to extract a structural generalization. They were unable to extract the same generalization using consonants, even when word segmentation was facilitated and the generalization made simpler. Our results suggest that different signal-driven computations prime lexical and grammatical processing.</description>
    <dc:title>Finding Words and Rules in a Speech Stream: Functional Differences Between Vowels and Consonants</dc:title>

    <dc:creator>Juan Toro</dc:creator>
    <dc:creator>Marina Nespor</dc:creator>
    <dc:creator>Jacques Mehler</dc:creator>
    <dc:creator>Luca Bonatti</dc:creator>
    <dc:identifier>doi:10.1111/j.1467-9280.2008.02059.x</dc:identifier>
    <dc:source>Psychological Science, Vol. 19, No. 2. (2008), pp. 137-144.</dc:source>
    <dc:date>2008-02-08T01:26:56-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Psychological Science</prism:publicationName>
    <prism:volume>19</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>137</prism:startingPage>
    <prism:endingPage>144</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2324683">
    <title>Neural Responses to Structural Incongruencies in Language and Statistical Learning Point to Similar Underlying Mechanisms</title>
    <link>http://www.citeulike.org/user/briordan/article/2324683</link>
    <description>&lt;i&gt;(2007), pp. 173-178.&lt;/i&gt;</description>
    <dc:title>Neural Responses to Structural Incongruencies in Language and Statistical Learning Point to Similar Underlying Mechanisms</dc:title>

    <dc:creator>Morten Christiansen</dc:creator>
    <dc:creator>Christopher Conway</dc:creator>
    <dc:creator>Luca Onnis</dc:creator>
    <dc:source>(2007), pp. 173-178.</dc:source>
    <dc:date>2008-02-03T03:10:08-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:startingPage>173</prism:startingPage>
    <prism:endingPage>178</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>erps</prism:category>
    <prism:category>semantic-association</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/1274140">
    <title>From the Cover: Brain signatures of artificial language processing: Evidence challenging the critical period hypothesis</title>
    <link>http://www.citeulike.org/user/briordan/article/1274140</link>
    <description>&lt;i&gt;PNAS, Vol. 99, No. 1. (8 January 2002), pp. 529-534.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Adult second language learning seems to be more difficult and less efficient than first language acquisition during childhood. By using event-related brain potentials, we show that adults who learned a miniature artificial language display a similar real-time pattern of brain activation when processing this language as native speakers do when processing natural languages. Participants trained in the artificial language showed two event-related brain potential components taken to reflect early automatic and late controlled syntactic processes, whereas untrained participants did not. This result challenges the common view that late second language learners process language in a principally different way from native speakers. Our findings demonstrate that a small system of grammatical rules can be syntactically instantiated by the adult speaker in a way that strongly resembles native-speaker sentence processing. 10.1073/pnas.012611199</description>
    <dc:title>From the Cover: Brain signatures of artificial language processing: Evidence challenging the critical period hypothesis</dc:title>

    <dc:creator>Angela Friederici</dc:creator>
    <dc:creator>Karsten Steinhauer</dc:creator>
    <dc:creator>Erdmut Pfeifer</dc:creator>
    <dc:identifier>doi:10.1073/pnas.012611199</dc:identifier>
    <dc:source>PNAS, Vol. 99, No. 1. (8 January 2002), pp. 529-534.</dc:source>
    <dc:date>2007-05-03T15:59:27-00:00</dc:date>
    <prism:publicationYear>2002</prism:publicationYear>
    <prism:publicationName>PNAS</prism:publicationName>
    <prism:volume>99</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>529</prism:startingPage>
    <prism:endingPage>534</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>erps</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/590852">
    <title>Statistical Learning by 8-Month-Old Infants</title>
    <link>http://www.citeulike.org/user/briordan/article/590852</link>
    <description>&lt;i&gt;Science, Vol. 274 (1996), pp. 1926-1928.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Learners rely on a combination of experience-independent and experience-dependent mechanisms to extract information from the environment. Language acquisition involves both types of mechanisms, but most theorists emphasize the relative importance of experience-independent mechanisms. The present study shows that a fundamental task of language acquisition, segmentation of words from fluent speech, can be accomplished by 8-month-old infants based solely on the statistical relationships between neighboring speech sounds. Moreover, this word segmentation was based on statistical learning from only 2 minutes of exposure, suggesting that infants have access to a powerful mechanism for the computation of statistical properties of the language input.</description>
    <dc:title>Statistical Learning by 8-Month-Old Infants</dc:title>

    <dc:creator>Jenny Saffran</dc:creator>
    <dc:creator>Richard Aslin</dc:creator>
    <dc:creator>Elissa Newport</dc:creator>
    <dc:source>Science, Vol. 274 (1996), pp. 1926-1928.</dc:source>
    <dc:date>2006-04-18T23:25:24-00:00</dc:date>
    <prism:publicationYear>1996</prism:publicationYear>
    <prism:publicationName>Science</prism:publicationName>
    <prism:volume>274</prism:volume>
    <prism:startingPage>1926</prism:startingPage>
    <prism:endingPage>1928</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/1366306">
    <title>Variability and Detection of Invariant Structure</title>
    <link>http://www.citeulike.org/user/briordan/article/1366306</link>
    <description>&lt;i&gt;Psychological Science, Vol. 13, No. 5. (2002), pp. 431-436.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Two experiments investigated learning of nonadjacent dependencies by adults and 18-month-olds. Each learner was exposed to three-element strings (e.g., pel-kicey-jic) produced by one of two artificial languages. Both languages contained the same adjacent dependencies, so learners could distinguish the languages only by acquiring dependencies between the first and third elements (the nonadjacent dependencies). The size of the pool from which the middle elements were drawn was systematically varied to investigate whether increasing variability (in the form of decreasing predictability between adjacent elements) would lead to better detection of nonadjacent dependencies. Infants and adults acquired nonadjacent dependencies only when adjacent dependencies were least predictable. The results point to conditions that might lead learners to focus on nonadjacent versus adjacent dependencies and are important for suggesting how learning might be dynamically guided by statistical structure.</description>
    <dc:title>Variability and Detection of Invariant Structure</dc:title>

    <dc:creator>Rebecca Gomez</dc:creator>
    <dc:identifier>doi:10.1111/1467-9280.00476</dc:identifier>
    <dc:source>Psychological Science, Vol. 13, No. 5. (2002), pp. 431-436.</dc:source>
    <dc:date>2007-06-05T21:25:53-00:00</dc:date>
    <prism:publicationYear>2002</prism:publicationYear>
    <prism:publicationName>Psychological Science</prism:publicationName>
    <prism:volume>13</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>431</prism:startingPage>
    <prism:endingPage>436</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2296228">
    <title>Distributional learning of syntactic categories</title>
    <link>http://www.citeulike.org/user/briordan/article/2296228</link>
    <description>&lt;i&gt;&lt;/i&gt;</description>
    <dc:title>Distributional learning of syntactic categories</dc:title>

    <dc:creator>Malathi Thothathiri</dc:creator>
    <dc:creator>Jesse Snedeker</dc:creator>
    <dc:date>2008-01-28T03:28:44-00:00</dc:date>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2286618">
    <title>Developing rich and quickly accessed knowledge of an artificial grammar</title>
    <link>http://www.citeulike.org/user/briordan/article/2286618</link>
    <description>&lt;i&gt;Memory &#38; Cognition, Vol. 35, No. 8. (December 2007), pp. 2118-2134.&lt;/i&gt;</description>
    <dc:title>Developing rich and quickly accessed knowledge of an artificial grammar</dc:title>

    <dc:creator>Bill Sallas</dc:creator>
    <dc:creator>Robert Mathews</dc:creator>
    <dc:creator>Sean Lane</dc:creator>
    <dc:creator>Ron Sun</dc:creator>
    <dc:source>Memory &#38; Cognition, Vol. 35, No. 8. (December 2007), pp. 2118-2134.</dc:source>
    <dc:date>2008-01-25T01:58:55-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Memory &#38; Cognition</prism:publicationName>
    <prism:volume>35</prism:volume>
    <prism:number>8</prism:number>
    <prism:startingPage>2118</prism:startingPage>
    <prism:endingPage>2134</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/945931">
    <title>Statistical Learning Within and Between Modalities: Pitting Abstract Against Stimulus-Specific Representations</title>
    <link>http://www.citeulike.org/user/briordan/article/945931</link>
    <description>&lt;i&gt;Psychological Science, Vol. 17, No. 10. (October 2006), pp. 905-912.&lt;/i&gt;</description>
    <dc:title>Statistical Learning Within and Between Modalities: Pitting Abstract Against Stimulus-Specific Representations</dc:title>

    <dc:creator>Christopher Conway</dc:creator>
    <dc:creator>Morten Christiansen</dc:creator>
    <dc:identifier>doi:10.1111/j.1467-9280.2006.01801.x</dc:identifier>
    <dc:source>Psychological Science, Vol. 17, No. 10. (October 2006), pp. 905-912.</dc:source>
    <dc:date>2006-11-16T05:19:28-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Psychological Science</prism:publicationName>
    <prism:issn>0956-7976</prism:issn>
    <prism:volume>17</prism:volume>
    <prism:number>10</prism:number>
    <prism:startingPage>905</prism:startingPage>
    <prism:endingPage>912</prism:endingPage>
    <prism:publisher>Blackwell Publishing</prism:publisher>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2164737">
    <title>Syntax constrains the acquisition of verb meaning</title>
    <link>http://www.citeulike.org/user/briordan/article/2164737</link>
    <description>&lt;i&gt;Language Learning and Development, Vol. 3, No. 4. (2007), pp. 325-341.&lt;/i&gt;</description>
    <dc:title>Syntax constrains the acquisition of verb meaning</dc:title>

    <dc:creator>Savita Bernal</dc:creator>
    <dc:creator>Jeffrey Lidz</dc:creator>
    <dc:creator>Severine Millotte</dc:creator>
    <dc:creator>Anne Christophe</dc:creator>
    <dc:source>Language Learning and Development, Vol. 3, No. 4. (2007), pp. 325-341.</dc:source>
    <dc:date>2007-12-25T03:06:18-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Language Learning and Development</prism:publicationName>
    <prism:volume>3</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>325</prism:startingPage>
    <prism:endingPage>341</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/312119">
    <title>Rule Learning by Seven-Month-Old Infants</title>
    <link>http://www.citeulike.org/user/briordan/article/312119</link>
    <description>&lt;i&gt;Science, Vol. 283, No. 5398. (01 January 1999), pp. 77-80.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;A fundamental task of language acquisition is to extract abstract algebraic rules. Three experiments show that 7-month-old infants attend longer to sentences with unfamiliar structures than to sentences with familiar structures. The design of the artificial language task used in these experiments ensured that this discrimination could not be performed by counting, by a system that is sensitive only to transitional probabilities, or by a popular class of simple neural network models. Instead, these results suggest that infants can represent, extract, and generalize abstract algebraic rules.</description>
    <dc:title>Rule Learning by Seven-Month-Old Infants</dc:title>

    <dc:creator>GF Marcus</dc:creator>
    <dc:creator>S Vijayan</dc:creator>
    <dc:creator>Bandi</dc:creator>
    <dc:creator>PM Vishton</dc:creator>
    <dc:identifier>doi:10.1126/science.283.5398.77</dc:identifier>
    <dc:source>Science, Vol. 283, No. 5398. (01 January 1999), pp. 77-80.</dc:source>
    <dc:date>2005-09-06T14:19:04-00:00</dc:date>
    <prism:publicationYear>1999</prism:publicationYear>
    <prism:publicationName>Science</prism:publicationName>
    <prism:volume>283</prism:volume>
    <prism:number>5398</prism:number>
    <prism:startingPage>77</prism:startingPage>
    <prism:endingPage>80</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2159951">
    <title>The role of prior experience in language acquisition</title>
    <link>http://www.citeulike.org/user/briordan/article/2159951</link>
    <description>&lt;i&gt;Cognitive Science, Vol. 31, No. 3. (2007), pp. 481-507.&lt;/i&gt;</description>
    <dc:title>The role of prior experience in language acquisition</dc:title>

    <dc:creator>Jill Lany‌</dc:creator>
    <dc:creator>Rebecca Gomez</dc:creator>
    <dc:creator>Lou Gerken‌</dc:creator>
    <dc:source>Cognitive Science, Vol. 31, No. 3. (2007), pp. 481-507.</dc:source>
    <dc:date>2007-12-22T18:49:23-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Cognitive Science</prism:publicationName>
    <prism:volume>31</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>481</prism:startingPage>
    <prism:endingPage>507</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/1194454">
    <title>Lexical configuration and lexical engagement: When adults learn new words</title>
    <link>http://www.citeulike.org/user/briordan/article/1194454</link>
    <description>&lt;i&gt;Cognitive Psychology, Vol. In Press, Corrected Proof&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;People know thousands of words in their native language, and each of these words must be learned at some time in the person's lifetime. A large number of these words will be learned when the person is an adult, reflecting the fact that the mental lexicon is continuously changing. We explore how new words get added to the mental lexicon, and provide empirical support for a theoretical distinction between what we call lexical configuration and lexical engagement. Lexical configuration is the set of factual knowledge associated with a word (e.g., the word's sound, spelling, meaning, or syntactic role). Almost all previous research on word learning has focused on this aspect. However, it is also critical to understand the process by which a word becomes capable of lexical engagement--the ways in which a lexical entry dynamically interacts with other lexical entries, and with sublexical representations. For example, lexical entries compete with each other during word recognition (inhibition within the lexical level), and they also support the activation of their constituents (top-down lexical-phonemic facilitation, and lexically-based perceptual learning). We systematically vary the learning conditions for new words, and use separate measures of lexical configuration and engagement. Several surprising dissociations in behavior demonstrate the importance of the theoretical distinction between configuration and engagement.</description>
    <dc:title>Lexical configuration and lexical engagement: When adults learn new words</dc:title>

    <dc:creator>Laura Leach</dc:creator>
    <dc:creator>Arthur Samuel</dc:creator>
    <dc:identifier>doi:10.1016/j.cogpsych.2007.01.001</dc:identifier>
    <dc:source>Cognitive Psychology, Vol. In Press, Corrected Proof</dc:source>
    <dc:date>2007-03-29T07:56:14-00:00</dc:date>
    <prism:publicationName>Cognitive Psychology</prism:publicationName>
    <prism:volume>In Press, Corrected Proof</prism:volume>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/310935">
    <title>The differential role of phonological and distributional cues in grammatical categorisation</title>
    <link>http://www.citeulike.org/user/briordan/article/310935</link>
    <description>&lt;i&gt;Cognition, Vol. 96, No. 2. (June 2005), pp. 143-182.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Recognising the grammatical categories of words is a necessary skill for the acquisition of syntax and for on-line sentence processing. The syntactic and semantic context of the word contribute as cues for grammatical category assignment, but phonological cues, too, have been implicated as important sources of information. The value of phonological and distributional cues has not, with very few exceptions, been empirically assessed. This paper presents a series of analyses of phonological cues and distributional cues and their potential for distinguishing grammatical categories of words in corpus analyses. The corpus analyses indicated that phonological cues were more reliable for less frequent words, whereas distributional information was most valuable for high frequency words. We tested this prediction in an artificial language learning experiment, where the distributional and phonological cues of categories of nonsense words were varied. The results corroborated the corpus analyses. For high-frequency nonwords, distributional information was more useful, whereas for low-frequency words there was more reliance on phonological cues. The results indicate that phonological and distributional cues contribute differentially towards grammatical categorisation.</description>
    <dc:title>The differential role of phonological and distributional cues in grammatical categorisation</dc:title>

    <dc:creator>Padraic Monaghan</dc:creator>
    <dc:creator>Nick Chater</dc:creator>
    <dc:creator>Morten Christiansen</dc:creator>
    <dc:identifier>doi:10.1016/j.cognition.2004.09.001</dc:identifier>
    <dc:source>Cognition, Vol. 96, No. 2. (June 2005), pp. 143-182.</dc:source>
    <dc:date>2005-09-02T16:01:15-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Cognition</prism:publicationName>
    <prism:volume>96</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>143</prism:startingPage>
    <prism:endingPage>182</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>cds</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/2105035">
    <title>A Bayesian framework for cross-situational word learning</title>
    <link>http://www.citeulike.org/user/briordan/article/2105035</link>
    <description>&lt;i&gt;&lt;/i&gt;</description>
    <dc:title>A Bayesian framework for cross-situational word learning</dc:title>

    <dc:creator>Michael Frank</dc:creator>
    <dc:creator>Noah Goodman</dc:creator>
    <dc:creator>Joshua Tenenbaum</dc:creator>
    <dc:date>2007-12-13T15:38:55-00:00</dc:date>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>bayesian</prism:category>
    <prism:category>cross-situational</prism:category>
    <prism:category>models</prism:category>
    <prism:category>word-learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/1260824">
    <title>Dog is a dog is a dog: Infant rule learning is not specific to language.</title>
    <link>http://www.citeulike.org/user/briordan/article/1260824</link>
    <description>&lt;i&gt;Cognition (22 December 2006)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Human infants possess powerful learning mechanisms used for the acquisition of language. To what extent are these mechanisms domain specific? One well-known infant language learning mechanism is the ability to detect and generalize rule-like similarity patterns, such as ABA or ABB [Marcus, G. F., Vijayan, S., Rao, S. B., &#38; Vishton, P. M. (1999). Rule learning by seven-month-old infants. Science, 283, 77-80.]. The results of three experiments demonstrate that 7-month-old infants can detect and generalize these same patterns when the elements consist of pictures of animals (dogs and cats). These findings indicate that rule learning of this type is not specific to language acquisition.</description>
    <dc:title>Dog is a dog is a dog: Infant rule learning is not specific to language.</dc:title>

    <dc:creator>Jenny R Saffran</dc:creator>
    <dc:creator>Seth D Pollak</dc:creator>
    <dc:creator>Rebecca L Seibel</dc:creator>
    <dc:creator>Anna Shkolnik</dc:creator>
    <dc:identifier>doi:10.1016/j.cognition.2006.11.004</dc:identifier>
    <dc:source>Cognition (22 December 2006)</dc:source>
    <dc:date>2007-04-27T17:21:38-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>Cognition</prism:publicationName>
    <prism:issn>0010-0277</prism:issn>
    <prism:category>artificial-grammars</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/1366461">
    <title>Learning at a distance II. Statistical learning of non-adjacent dependencies in a non-human primate</title>
    <link>http://www.citeulike.org/user/briordan/article/1366461</link>
    <description>&lt;i&gt;Cognitive Psychology, Vol. 49, No. 2. (September 2004), pp. 85-117.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;In earlier work we have shown that adults, infants, and cotton-top tamarin monkeys are capable of computing the probability with which syllables occur in particular orders in rapidly presented streams of human speech, and of using these probabilities to group adjacent syllables into word-like units. We have also investigated adults' learning of regularities among elements that are not adjacent, and have found strong selectivities in their ability to learn various kinds of non-adjacent regularities. In the present paper we investigate the learning of these same non-adjacent regularities in tamarin monkeys, using the same materials and familiarization methods. Three types of languages were constructed. In one, words were formed by statistical regularities between non-adjacent syllables. Words contained predictable relations between syllables 1 and 3; syllable 2 varied. In a second type of language, words were formed by statistical regularities between non-adjacent segments. Words contained predictable relations between consonants; the vowels varied. In a third type of language, also formed by regularities between non-adjacent segments, words contained predictable relations between vowels; the consonants varied. Tamarin monkeys were exposed to these languages in the same fashion as adults (21 min of exposure to a continuous speech stream) and were then tested in a playback paradigm measuring spontaneous looking (no reinforcement). Adult subjects learned the second and third types of language easily, but failed to learn the first. However, tamarin monkeys showed a different pattern, learning the first and third type of languages but not the second. These differences held up over multiple replications, using different sounds instantiating each of the patterns. These results suggest differences among learners in the elementary units perceived in speech (syllables, consonants, and vowels) and/or the distance over which such units can be related, and therefore differences among learners in the types of patterned regularities they can acquire. Such studies with tamarins open interesting questions about the perceptual and computational capacities of human learners that may be essential for language acquisition, and how they may differ from those of non-human primates.</description>
    <dc:title>Learning at a distance II. Statistical learning of non-adjacent dependencies in a non-human primate</dc:title>

    <dc:creator>Elissa Newport</dc:creator>
    <dc:creator>Marc Hauser</dc:creator>
    <dc:creator>Geertrui Spaepen</dc:creator>
    <dc:creator>Richard Aslin</dc:creator>
    <dc:identifier>doi:10.1016/j.cogpsych.2003.12.002</dc:identifier>
    <dc:source>Cognitive Psychology, Vol. 49, No. 2. (September 2004), pp. 85-117.</dc:source>
    <dc:date>2007-06-05T22:10:05-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:publicationName>Cognitive Psychology</prism:publicationName>
    <prism:volume>49</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>85</prism:startingPage>
    <prism:endingPage>117</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/1366465">
    <title>Learning at a distance I. Statistical learning of non-adjacent dependencies</title>
    <link>http://www.citeulike.org/user/briordan/article/1366465</link>
    <description>&lt;i&gt;Cognitive Psychology, Vol. 48, No. 2. (March 2004), pp. 127-162.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;In earlier work we have shown that adults, young children, and infants are capable of computing transitional probabilities among adjacent syllables in rapidly presented streams of speech, and of using these statistics to group adjacent syllables into word-like units. In the present experiments we ask whether adult learners are also capable of such computations when the only available patterns occur in non-adjacent elements. In the first experiment, we present streams of speech in which precisely the same kinds of syllable regularities occur as in our previous studies, except that the patterned relations among syllables occur between non-adjacent syllables (with an intervening syllable that is unrelated). Under these circumstances we do not obtain our previous results: learners are quite poor at acquiring regular relations among non-adjacent syllables, even when the patterns are objectively quite simple. In subsequent experiments we show that learners are, in contrast, quite capable of acquiring patterned relations among non-adjacent segments--both non-adjacent consonants (with an intervening vocalic segment that is unrelated) and non-adjacent vowels (with an intervening consonantal segment that is unrelated). Finally, we discuss why human learners display these strong differences in learning differing types of non-adjacent regularities, and we conclude by suggesting that these contrasts in learnability may account for why human languages display non-adjacent regularities of one type much more widely than non-adjacent regularities of the other type.</description>
    <dc:title>Learning at a distance I. Statistical learning of non-adjacent dependencies</dc:title>

    <dc:creator>Elissa Newport</dc:creator>
    <dc:creator>Richard Aslin</dc:creator>
    <dc:identifier>doi:10.1016/S0010-0285(03)00128-2</dc:identifier>
    <dc:source>Cognitive Psychology, Vol. 48, No. 2. (March 2004), pp. 127-162.</dc:source>
    <dc:date>2007-06-05T22:10:46-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:publicationName>Cognitive Psychology</prism:publicationName>
    <prism:volume>48</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>127</prism:startingPage>
    <prism:endingPage>162</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/1832240">
    <title>Acquiring and processing verb argument structure: Distributional learning in a miniature language</title>
    <link>http://www.citeulike.org/user/briordan/article/1832240</link>
    <description>&lt;i&gt;Cognitive Psychology, Vol. 56, No. 3. (May 2008), pp. 165-209.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Adult knowledge of a language involves correctly balancing lexically-based and more language-general patterns. For example, verb argument structures may sometimes readily generalize to new verbs, yet with particular verbs may resist generalization. From the perspective of acquisition, this creates significant learnability problems, with some researchers claiming a crucial role for verb semantics in the determination of when generalization may and may not occur. Similarly, there has been debate regarding how verb-specific and more generalized constraints interact in sentence processing and on the role of semantics in this process. The current work explores these issues using artificial language learning. In three experiments using languages without semantic cues to verb distribution, we demonstrate that learners can acquire both verb-specific and verb-general patterns, based on distributional information in the linguistic input regarding each of the verbs as well as across the language as a whole. As with natural languages, these factors are shown to affect production, judgments and real-time processing. We demonstrate that learners apply a rational procedure in determining their usage of these different input statistics and conclude by suggesting that a Bayesian perspective on statistical learning may be an appropriate framework for capturing our findings.</description>
    <dc:title>Acquiring and processing verb argument structure: Distributional learning in a miniature language</dc:title>

    <dc:creator>Elizabeth Wonnacott</dc:creator>
    <dc:creator>Elissa Newport</dc:creator>
    <dc:creator>Michael Tanenhaus</dc:creator>
    <dc:identifier>doi:10.1016/j.cogpsych.2007.04.002</dc:identifier>
    <dc:source>Cognitive Psychology, Vol. 56, No. 3. (May 2008), pp. 165-209.</dc:source>
    <dc:date>2007-10-28T14:00:28-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>Cognitive Psychology</prism:publicationName>
    <prism:volume>56</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>165</prism:startingPage>
    <prism:endingPage>209</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
    <prism:category>statistical-learning</prism:category>
    <prism:category>syntactic-acquisition</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/832677">
    <title>Acquisition of Gender-like Noun Subclasses in an Artificial Language: The Contribution of Phonological Markers to Learning</title>
    <link>http://www.citeulike.org/user/briordan/article/832677</link>
    <description>&lt;i&gt;Journal of Memory and Language, Vol. 32, No. 1. (February 1993), pp. 76-95.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Many languages contain apparently arbitrary word classes, of which the best known examples are the gender classes of languages such as French, Hebrew, and Italian. However, a number of phonological or semantic similarities typically exist among subsets of class members which could assist the language learner in discovering the class distinction. The primary objective of this study was to investigate the possibly facilitative role of phonological similarities among a subset of class members in the acquisition of otherwise arbitrary word classes, using artificial miniature languages. The learning of an experimental language in which a subset of the members of each noun class shared a set of phonological features (i.e., a common ending) was compared with the learning of a control language in which phonological similarities were randomly distributed between the two noun classes. Many adult subjects learning the experimental language acquired the word classes while no one learning the control language did. The results were replicated with nine- and ten-year-old children. These findings support an acquisition model in which inherent similarities among words are the means by which the classes are discovered; they cast doubt on models with mechanisms for acquiring completely arbitrary classes.</description>
    <dc:title>Acquisition of Gender-like Noun Subclasses in an Artificial Language: The Contribution of Phonological Markers to Learning</dc:title>

    <dc:creator>Brooks</dc:creator>
    <dc:creator>Braine</dc:creator>
    <dc:creator>Catalano Lisa</dc:creator>
    <dc:creator>Brody</dc:creator>
    <dc:creator>Sudhalter Vicki</dc:creator>
    <dc:identifier>doi:10.1006/jmla.1993.1005</dc:identifier>
    <dc:source>Journal of Memory and Language, Vol. 32, No. 1. (February 1993), pp. 76-95.</dc:source>
    <dc:date>2006-09-06T16:58:17-00:00</dc:date>
    <prism:publicationYear>1993</prism:publicationYear>
    <prism:publicationName>Journal of Memory and Language</prism:publicationName>
    <prism:volume>32</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>76</prism:startingPage>
    <prism:endingPage>95</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/briordan/article/832687">
    <title>Exploring language acquisition in children with a miniature artificial language: Effects of item and pattern frequency, arbitrary subclasses, and correction</title>
    <link>http://www.citeulike.org/user/briordan/article/832687</link>
    <description>&lt;i&gt;Journal of Memory and Language, Vol. 29, No. 5. (October 1990), pp. 591-610.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Very little of the artificial language experimentation in the literature has been done with children, although children are the primary target population to which experimenters wish to generalize. For this reason, we used children (7-10 years old) to explore the acquisition of a miniature artificial language with rules, patterns, subpatterns, and exceptions that are quite like those found in inflectional systems of natural languages. The first goal of the study was to explore two aspects of linguistic input--how frequency of presentation affects the relative roles of rote and rule or pattern learning, and the learnability of arbitrary subclasses. A second goal was to determine the effects of immediate corrective feedback on acquisition; and a third goal was to examine adult-child differences in learning. Overwhelmingly, the children learned via rules rather than by rote, but failed to distinguish the arbitrary subclasses. Frequency of presentation had specific effects on the acquisition of items and patterns. The immediacy of feedback had no significant effect on learning. Although there was a small (though significant) difference between the performance of the children and that of some adult subjects, overall, the results support the existence of a class of pattern learning skills that is common to children and adults and includes some aspects of syntax acquisition.</description>
    <dc:title>Exploring language acquisition in children with a miniature artificial language: Effects of item and pattern frequency, arbitrary subclasses, and correction</dc:title>

    <dc:creator>Martin Braine</dc:creator>
    <dc:creator>Ruth Brody</dc:creator>
    <dc:creator>Patricia Brooks</dc:creator>
    <dc:creator>Vicki Sudhalter</dc:creator>
    <dc:creator>Julie Ross</dc:creator>
    <dc:creator>Lisa Catalano</dc:creator>
    <dc:creator>Shalom Fisch</dc:creator>
    <dc:identifier>doi:10.1016/0749-596X(90)90054-4</dc:identifier>
    <dc:source>Journal of Memory and Language, Vol. 29, No. 5. (October 1990), pp. 591-610.</dc:source>
    <dc:date>2006-09-06T17:01:48-00:00</dc:date>
    <prism:publicationYear>1990</prism:publicationYear>
    <prism:publicationName>Journal of Memory and Language</prism:publicationName>
    <prism:volume>29</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>591</prism:startingPage>
    <prism:endingPage>610</prism:endingPage>
    <prism:category>artificial-grammars</prism:category>
</item>



</rdf:RDF>

