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Working Memory in Sentence Comprehension: Processing Hindi Center Embeddings [Kõva köide]

  • Formaat: Hardback, 290 pages, kõrgus x laius: 229x152 mm, kaal: 1230 g
  • Ilmumisaeg: 09-May-2003
  • Kirjastus: Routledge
  • ISBN-10: 0415967619
  • ISBN-13: 9780415967617
Teised raamatud teemal:
  • Formaat: Hardback, 290 pages, kõrgus x laius: 229x152 mm, kaal: 1230 g
  • Ilmumisaeg: 09-May-2003
  • Kirjastus: Routledge
  • ISBN-10: 0415967619
  • ISBN-13: 9780415967617
Teised raamatud teemal:
The first-ever investigation of sentence processing in Hindi, Working Memory in Sentence Comprehension studies the predictions of three existing, wide-coverage sentence processing models. In experiments that apply these models to Hindi, Shravan Vasishth develops a new sentence processing model that builds on existing theories and overcomes their empirical problems. Advancing the understanding of human parsing processes, this book is a landmark in cross-linguistic research, presenting a challenging set of sentence processing facts that will impact future theories.
List of Tables
xi
List of Figures
xvii
List of Algorithms
xxiii
Acknowledgments xxv
Preface xxvii
Introduction
3(30)
Self-center embeddings and sentence processing
4(5)
Self-center embeddings in Hindi
9(15)
Some syntactic properties of self-center embeddings
9(1)
Semantics/pragmatics: Differential Object Marking in Hindi
10(14)
Case-marked objects are specific, but conversationally implicate definiteness
24(2)
Bare singular NPs really are indefinites
26(7)
Dayal's arguments against treating bare singular NPs as indefinites
27(1)
Alternative explanations for the Hindi facts
28(5)
Three models of sentence processing
33(22)
Hawkins' Early Immediate Constituents (1994, 1998)
33(7)
Gibson's Dependency Locality Theory (2000)
40(3)
Lewis' Retrieval Interference Theory
43(12)
Retrieval Interference Theory, 2001 (RIT-01)
43(6)
Retrieval Interference Theory, 2002 (RIT-02)
49(6)
The effect of identical case marking
55(48)
Experiment 1
56(4)
Method and Procedure
56(3)
Results
59(1)
Discussion
59(1)
Experiment 2
60(15)
Method
61(3)
Results
64(9)
Discussion
73(2)
Experiment 3
75(28)
Method
78(2)
Results: The effect of definite -ko with no other ko-marked NPs present
80(4)
Results: The effect of definite -ko with a non-adjacent ko-marked indirect object present
84(4)
Results: The effect of adjacent se-marked NPs versus non-adjacent ko-marked NPs
88(3)
Results: The effect of multiple se-marking
91(3)
Results: The effect of adjaceny on positional similarity
94(3)
Results: The effect of adjacent, dative case-marked NPs
97(3)
Discussion
100(3)
Distance effects or similarity-based interference?
103(44)
Experiment 4
106(3)
Method
106(1)
Results
107(1)
Discussion
108(1)
Experiment 5: Indirect-object fronting
109(20)
Method
111(1)
Results: The effect of definiteness marking (canonical word order)
112(4)
Results: The effect of definiteness marking (fronted indirect objects)
116(4)
Results: The effect of increasing distance between a verb and its arguments (bare direct object)
120(3)
Results: The effect of increasing distance between a verb and its arguments (definite-marked direct object)
123(3)
Discussion
126(3)
Experiment 6: Direct-object fronting
129(18)
Method
129(1)
Results: The effect of definiteness marking (canonical order)
130(5)
Results: The effect of definiteness marking (direct object fronted)
135(4)
Results: The effect of direct-object fronting (bare direct object)
139(2)
Results: The effect of direct-object fronting (definite-marked direct object)
141(2)
Discussion
143(4)
Increasing distance can facilitate processing
147(12)
Method
148(1)
Subjects
148(1)
Materials and Procedure
148(1)
Results: Adverb insertion in single embeddings
149(3)
Results: Adverb insertion in double embeddings
152(2)
Discussion
154(5)
Word length, position, and reading time
159(28)
Hindi orthography
160(2)
Does word length affect reading time in Hindi?
162(8)
Computing word length for Hindi
162(1)
Reading time and word length -- results from Experiment 2
163(6)
Correcting for word length
169(1)
Does position affect reading time?
170(17)
Concluding remarks, and a new sentence processing model
187(38)
Multiple constraints in language processing: A summing up
187(5)
A model of sentence processing based on abductive inference
192(28)
The underlying competence grammar G
193(1)
The set H of hypothesis formers
194(2)
Some definitions
196(3)
The algorithm
199(2)
The complexity metric
201(4)
Computational properties of the abductive parser
205(2)
Empirical coverage of AIM
207(12)
The connection between the abduction-based model and the complexity metric; and integrating AIM, DLT, and RIT
219(1)
Some shortcomings of the present model
220(5)
A Stimuli
225(18)
Experiment 1
226(2)
Experiment 2
228(2)
Experiment 3
230(6)
Experiment 4
236(1)
Experiments 5 and 6
237(2)
Experiment 7
239(4)
Index 243(4)
References 247


Shravan Vasishth is co-editor of the Seventh Edition of the Language Files, published by the Ohio State University of Press. He is currently a researcher in the Department of Computational Linguistics at Saarland University, Germany.