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Simple Search
Hits 1 – 11 of 11
1
The biological and cultural foundations of language.
Reali, F
;
Christiansen, MH
;
Chater, N
In: Commun Integr Biol , 2 (3) pp. 221-222. (2009) (2009)
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2
Restrictions on biological adaptation in language evolution
Chater, N
;
Reali, F
;
Christiansen, MH
In: P NATL ACAD SCI USA , 106 (4) 1015 - 1020. (2009) (2009)
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3
Language as shaped by the brain
Christiansen, MH
;
Chater, N
In: BEHAV BRAIN SCI , 31 (5) 489 - 509. (2008) (2008)
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4
The phonological-distributional coherence hypothesis: Cross-linguistic evidence in language acquisition
Monaghan, P
;
Christiansen, MH
;
Chater, N
In: COGNITIVE PSYCHOL , 55 (4) 259 - 305. (2007) (2007)
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5
The differential role of phonological and distributional cues in grammatical categorisation
Monaghan, P
;
Chater, N
;
Christiansen, MH
In: COGNITION , 96 (2) 143 - 182. (2005) (2005)
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6
Connectionist psycholinguistics: capturing the empirical data
Christiansen, MH
;
Chater, N
In: TRENDS COGN SCI , 5 (2) 82 - 88. (2001) (2001)
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7
Connectionist psycholinguistics: The very idea.
Christiansen, MH
;
Chater, N
In: In: Christiansen, MH and Chater, N, (eds.) Connectionist psycholinguistics. (pp. 1-15). Ablex: Westport,CT. (2001) (2001)
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8
Finite models of infinite language: A connectionist approach to recursion
Christiansen, MH
;
Chater, N
In: In: Christiansen, MH and Chater, N, (eds.) Connectionist psycholinguistics. (pp. 138-176). Ablex: Westport, CT. (2001) (2001)
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9
Connectionist psycholinguistics in perspective
Christiansen, MH
;
Chater, N
In: In: Christiansen, MH and Chater, N, (eds.) Connectionist psycholinguistics. (pp. 19-75). Ablex: Westport, CT. (2001) (2001)
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10
Connectionist natural language processing: The state of the art
Christiansen, MH
;
Chater, N
In: COGNITIVE SCI , 23 (4) 417 - 437. (1999) (1999)
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11
Toward a connectionist model of recursion in human linguistic performance
Christiansen, MH
;
Chater, N
In: COGNITIVE SCI , 23 (2) 157 - 205. (1999) (1999)
Abstract:
Naturally occurring speech contains only a limited amount of complex recursive structure, and this is reflected in the empirically documented difficulties that people experience when processing such structures. We present a connectionist model of human performance in processing recursive language structures. The model is trained on simple artificial languages. We find that the qualitative performance profile of the model matches human behavior, both on the relative difficulty of center-embedding and cross-dependency, and between the processing of these complex recursive structures and right-branching recursive constructions; We analyze how these differences in performance are reflected in the internal representations of the model by performing discriminant analyses on these representations both before and after training. Furthermore, we show how a network trained to process recursive structures can also generate such structures in a probabilistic fashion. This work suggests a novel explanation of people's limited recursive performance, without assuming the existence of a mentally represented competence grammar allowing unbounded recursion.
Keyword:
DEPENDENCIES
;
DISTRIBUTED REPRESENTATIONS
;
INDIVIDUAL-DIFFERENCES
;
LANGUAGE
;
NEURAL NETWORKS
;
SAUSAGE MACHINE
;
SIMPLE RECURRENT NETWORKS
;
WORKING MEMORY
URL:
http://discovery.ucl.ac.uk/124983/
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