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Sentence Comprehension as a Cognitive Process: A Computational Approach [Kõva köide]

(Universität Potsdam, Germany), (Universität Potsdam, Germany)
  • Formaat: Hardback, 300 pages, kõrgus x laius x paksus: 235x158x20 mm, kaal: 510 g
  • Ilmumisaeg: 11-Nov-2021
  • Kirjastus: Cambridge University Press
  • ISBN-10: 1107133114
  • ISBN-13: 9781107133112
Teised raamatud teemal:
Sentence Comprehension as a Cognitive Process: A Computational ApproachSuurem pilt
  • Formaat: Hardback, 300 pages, kõrgus x laius x paksus: 235x158x20 mm, kaal: 510 g
  • Ilmumisaeg: 11-Nov-2021
  • Kirjastus: Cambridge University Press
  • ISBN-10: 1107133114
  • ISBN-13: 9781107133112
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781107133112.html
Märksõnad:
"Sentence comprehension - the way we process and understand spoken and written language - is a central and important area of research within psycholinguistics. This book explores the contribution of computational linguistics to the field, showing how computational models of sentence processing can help scientists in their investigation of human cognitive processes. It presents the leading computational model of retrieval processes in sentence processing, the Lewis and Vasishth cue-based retrieval mode, and develops a principled methodology for parameter estimation and model comparison/evaluation using benchmark data, to enable researchers to test their own models of retrieval against the present model. It also provides readers with an overview of the last 20 years of research on the topic of retrieval processes in sentence comprehension, along with source code that allows researchers to extend the model and carry out new research. Comprehensive in its scope, this book is essential reading for researchersin cognitive science"--

Muu info

Presents a computational model of sentence processing that is grounded in decades of research in cognitive psychology and AI.
List of Figures ix
List of Tables xvii
Foreword xx
Richard L. Lewis
Preface xxiii
Acknowledgements xxiv
1 Introduction 1(20)
1.1 Working Memory in Theories of Sentence Comprehension
2(4)
1.2 Prediction in Sentence Processing
6(1)
1.3 Working Memory and Prediction as Explanations for Processing Difficulty
7(1)
1.4 Current Beliefs about Constraints on Sentence Comprehension
7(1)
1.5 Some Gaps in the Sentence Processing Literature
8(8)
1.5.1 The Relative Scarcity of Computationally Implemented Models
8(2)
1.5.2 A Focus on Average Behaviour and Neglect of Individual-Level Differences
10(1)
1.5.3 The Absence of High-Precision Studies
11(1)
1.5.4 Unclear Desiderata for a Good Model Fit
11(5)
1.6 The Goals of This Book
16(3)
1.6.1 Providing Open Source Model Code
17(1)
1.6.2 Modelling Average Effects as Well as Individual Differences
17(1)
1.6.3 Developing a Set of Modelling and Empirical Benchmarks for Future Model Comparison
18(1)
1.7 Looking Ahead
19(2)
2 Dependencies in Sentence Comprehension 21(28)
2.1 Memory Processes in Sentence Comprehension
21(2)
2.2 Dependency Completion in Sentence Processing
23(3)
2.3 Subject-Verb Non-Agreement Dependencies
26(5)
2.4 Subject-Verb Number Agreement
31(7)
2.5 Reflexives and Reciprocals
38(9)
2.5.1 Individual-Level Effects in the Dillon et al. Design
44(1)
2.5.2 A Sensitivity Analysis on the Ungrammatical Agreement and Reflexives Conditions Using Informative Priors
44(3)
2.6 Concluding Remarks
47(2)
3 The Core ACT-R-Based Model of Retrieval Processes 49(22)
3.1 ACT-R
49(3)
3.2 The Lewis and Vasishth (2005) Model
52(11)
3.2.1 A Priori Predictions of the Model
54(6)
3.2.2 Comparison of the LV05 Prediction Space with the Results of the Jager et al. Meta-analysis
60(3)
3.3 A More Principled Approach to Parameter Estimation
63(6)
3.3.1 Bayesian Parameter Estimation
64(2)
3.3.2 Approximate Bayesian Computation
66(3)
3.4 Concluding Remarks
69(2)
4 An Extension of the Core Model: Modelling Prominence and Multi-associative Cues 71(45)
4.1 Incorporating Prominence and Multi-associative Cues
72(22)
4.1.1 Item Prominence
74(10)
4.1.2 Multi-associative Cues
84(5)
4.1.3 Implementation of Item Prominence and Multi-associative Cues
89(1)
4.1.4 Multi-associative Cues
90(3)
4.1.5 Prominence
93(1)
4.2 A Simulation of the Meta-analysis Studies
94(9)
4.2.1 Data
95(1)
4.2.2 Method
95(3)
4.2.3 Results
98(5)
4.3 Discussion
103(8)
4.3.1 Distractor Prominence
107(1)
4.3.2 Multi-associative Cues
108 (3)
Appendices
4.A Key Terms and Concepts
111(2)
4.B List of Experiments Included in the Simulations
113(1)
4.C Model Specifications
114(2)
5 An Extension of the Core Model: Modelling the Interaction of Eye-Movement Control and Parsing 116(24)
5.1 The EMMA/ACT-R Reading Model
118(1)
5.2 Replication of Salvucci (2001)
119(3)
5.2.1 Data
119(1)
5.2.2 Model
120(1)
5.2.3 Analysis
120(2)
5.2.4 Results
122(1)
5.2.5 Discussion
122(1)
5.3 The Extended EMMA/ACT-R Model
122(3)
5.3.1 Surprisal
124(1)
5.4 Simulations on the Potsdam Sentence Corpus
125(7)
5.4.1 Data
126(1)
5.4.2 Model
127(1)
5.4.3 Results
128(3)
5.4.4 Discussion
131(1)
5.5 General Discussion
132(4)
5.5.1 Comparison with E-Z Reader
132(2)
5.5.2 Future Prospects
134(2)
Appendices
5.A Root-Mean-Square Deviation
136(1)
5.B Linear Regression Analysis
136(4)
6 Reanalysis and Underspecification in Sentence Comprehension: Modelling Eye Movements 140(21)
6.1 Introduction
140(1)
6.2 Modelling Reanalysis: Memory and Expectation Processes in Parsing
141(7)
6.2.1 Memory and Expectation in Relative Clauses
141(2)
6.2.2 Simulation: Modelling the Staub (2010) Data
143(1)
6.2.3 Results
144(1)
6.2.4 Discussion
145(3)
6.3 Modelling Underspecification: The Adaptive Interaction between Parsing, Eye-Movement Control, and Working Memory Capacity
148(12)
6.3.1 Good-Enough Parsing
148(5)
6.3.2 Simulation: Modelling the von der Malsburg and Vasishth (2013) Experiment
153(1)
6.3.3 Results
154(3)
6.3.4 Discussion
157(3)
6.4 General Discussion
160(1)
7 Competing Accounts of Interference in Sentence Processing 161(17)
7.1 The Direct-Access Model
161(3)
7.2 Comparing the Predictive Performance of the Models
164(7)
7.2.1 Inhibitory Interference
164(3)
7.2.2 Relative Clauses in Chinese
167(3)
7.2.3 Discussion
170(1)
7.3 Encoding Interference in Agreement Attraction
171(5)
7.3.1 An Evaluation of the Nairne Proposal
173(1)
7.3.2 Model Comparison
174(1)
7.3.3 Discussion
175(1)
7.4 Summary
176(2)
8 Modelling Sentence Comprehension Deficits in Aphasia 178(22)
8.1 Theories and Models of Sentence Comprehension Deficits
178(9)
8.1.1 Timing Deficit
179(1)
8.1.2 Reduction in Memory
180(1)
8.1.3 Intermittent Deficiency
181(1)
8.1.4 Weakened Syntax
182(1)
8.1.5 Slow Syntax
183(1)
8.1.6 Lexical Integration Deficit
184(1)
8.1.7 Lexical Access Deficits
184(1)
8.1.8 A Comparison of Theories of Impaired Processing, and Their Relation to Theories of Unimpaired Processing
185(2)
8.2 Modelling Individual-Level Differences
187(10)
8.2.1 Mapping ACT-R Parameters to Sources of Deficits
189(2)
8.2.2 Simulations
191(1)
8.2.3 Results
192(3)
8.2.4 Discussion
195(2)
8.3 Competing Models of Retrieval in Aphasia
197(1)
8.3.1 Materials
197(1)
8.3.2 Results and Discussion
198(1)
8.4 Concluding Remarks
198(2)
9 Future Directions 200(3)
9.1 Developing Implemented Computational Models
200(1)
9.2 An Excessive Focus on Average Behaviour
200(1)
9.3 Creating Higher-Precision Benchmark Data-Sets for Model Evaluation and Comparison
201(1)
9.4 Developing Better Criteria for Evaluating Model Fit
202(1)
9.5 In Closing
202(1)
Bibliography 203(18)
Index 221
Shravan Vasishth is Professor of Linguistics at the University of Potsdam. He is also a chartered statistician (Royal Statistical Society). Felix Engelmann is co-founder and data scientist at the business analytics company, startupdetector. His published research applies diverse computational methods to the modelling of human language processing and language acquisition.