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Language, Cognition, and Computational Models [Kõva köide]

Edited by (Centre National de la Recherche Scientifique (CNRS), Paris), Edited by (Universidade Federal do Rio Grande do Sul, Brazil)
  • Formaat: Hardback, 336 pages, kõrgus x laius x paksus: 235x158x25 mm, kaal: 600 g
  • Sari: Studies in Natural Language Processing
  • Ilmumisaeg: 25-Jan-2018
  • Kirjastus: Cambridge University Press
  • ISBN-10: 110716222X
  • ISBN-13: 9781107162228
  • Formaat: Hardback, 336 pages, kõrgus x laius x paksus: 235x158x25 mm, kaal: 600 g
  • Sari: Studies in Natural Language Processing
  • Ilmumisaeg: 25-Jan-2018
  • Kirjastus: Cambridge University Press
  • ISBN-10: 110716222X
  • ISBN-13: 9781107162228
How do infants learn a language? Why and how do languages evolve? How do we understand a sentence? This book explores these questions using recent computational models that shed new light on issues related to language and cognition. The chapters in this collection propose original analyses of specific problems and develop computational models that have been tested and evaluated on real data. Featuring contributions from a diverse group of experts, this interdisciplinary book bridges the gap between natural language processing and cognitive sciences. It is divided into three sections, focusing respectively on models of neural and cognitive processing, data driven methods, and social issues in language evolution. This book will be useful to any researcher and advanced student interested in the analysis of the links between the brain and the language faculty.

Featuring contributions from a diverse group of experts, this book explores issues related to language and cognition using recent computational models. It proposes original analyses and develops computational models that have been tested and evaluated on real data. The book will be useful to researchers and graduate students.

Arvustused

'The deepest questions about language will be solved through cooperation across disciplinary boundaries. Insights from neuroscience, psychology, linguistics, and social science only offer partial explanations. Computer modeling provides an ideal methodology to integrate these diverse insights and put them to the test on real data. This broad collection of papers from leading research groups, contextualised by Thierry Poibeau and Aline Villavicencio, will inspire everyone interested in the cognitive aspects of language processing.' Walter Daelemans, Universiteit Antwerpen 'Although Natural Language Processing could be considered an area of Cognitive Science, the two fields have tended to go their own way as they matured. Yet the interaction between the two areas can be fruitful. Poibeau and Villavicencio have to be credited for playing an important role in keeping the connection between the two fields alive. The well-chosen and insightful papers in this book provide a great illustration of how the interaction between the two fields can lead to progress in a number of areas from language acquisition to parsing to the diagnosis of cognitive deficits, to the new area of using language models to gain insights about how the brain encodes semantics, and vice versa.' Massimo Poesio, Queen Mary University of London 'This volume brings a uniquely interdisciplinary approach to its subjects All of the essays present new and emerging research in neuroscience and language. While the materials covered are advanced for most undergraduates, this volume would make a valuable resource for researchers in the field and a helpful guide to graduate students on subjects for further research. An excellent addition to collections where natural language processing and cognitive science are studied. Summing Up: Recommended.' R. Bharath, Choice

Muu info

This book uses recent computational models to explore issues related to language and cognition.
Figures
ix
Tables
xi
Contributors xv
Part I About This Book
1 Introduction: Cognitive Issues in Natural Language Processing
3(24)
Thierry Poibeau
Aline Villavicencio
1.1 On the Relationships between Natural Language Processing and Cognitive Sciences
3(5)
1.2 Recent Issues in Cognitive Aspects of Language Modeling
8(6)
1.3 Content and Structure of the Book
14(13)
Part II Models of Neural and Cognitive Processing
2 Light and Deep Parsing: A Cognitive Model of Sentence Processing
27(26)
Philippe Blache
2.1 Introduction
27(1)
2.2 An Interdisciplinary View of Language Processing
28(11)
2.3 The Theoretical Framework: Property Grammars
39(3)
2.4 Chunks, Constructions, and Properties
42(4)
2.5 The Hybrid Architecture
46(3)
2.6 Conclusion
49(4)
3 Decoding Language from the Brain
53(28)
Brian Murphy
Leila Wehbe
Alona Fyshe
3.1 Introduction
53(2)
3.2 Grounding Language Architecture in the Brain
55(7)
3.3 Decoding Words in the Brain
62(4)
3.4 Phrases in the Brain
66(2)
3.5 Stories in the Brain
68(4)
3.6 Summary
72(9)
4 Graph Theory Applied to Speech: Insights on Cognitive Deficit Diagnosis and Dream Research
81(20)
Natalia Bezerra Mota
Mauro Copelli
Sidarta Ribeiro
4.1 Introduction
82(2)
4.2 Semantic Analysis for the Diagnosis of Psychosis
84(1)
4.3 What Is a Speech Graph?
85(3)
4.4 Speech Graphs as a Strategy to Quantify Symptoms on Psychosis
88(4)
4.5 Differences in Speech Graphs due to Content (waking × dream reports)
92(2)
4.6 Speech Graphs Applied to Dementia
94(2)
4.7 Future Perspectives
96(5)
Part III Data Driven Models
5 Putting Linguistics Back into Computational Linguistics
101(17)
Martin Kay
5.1 Explicit and Implicit Information
101(7)
5.2 Features
108(6)
5.3 Linguistic Computation and Computational Linguistics
114(2)
5.4 Conclusion
116(2)
6 A Distributional Model of Verb-Specific Semantic Roles Inferences
118(41)
Gianluca E. Lebani
Alessandro Lenci
6.1 Representing and Acquiring Thematic Roles
119(3)
6.2 Characterizing the Semantic Content of Verb Proto-roles
122(8)
6.3 A Distributional Model of Thematic Roles
130(9)
6.4 Experiments with Our Neo-Davidsonian Model
139(9)
6.5 Conclusion
148(11)
7 Native Language Identification on EFCAMDAT
159(26)
Xiao Jiang
Yan Huang
Yufan Guo
Jeroen Geertzen
Theodora Alexopoulou
Lin Sun
Anna Korhonen
7.1 Introduction
159(6)
7.2 Data
165(3)
7.3 Methods
168(4)
7.4 Results
172(9)
7.5 Conclusion
181(4)
8 Evaluating Language Acquisition Models: A Utility-Based Look at Bayesian Segmentation
185(42)
Lisa Pearl
Lawrence Phillips
8.1 Introduction
185(2)
8.2 Early Speech Segmentation
187(3)
8.3 A Bayesian Segmentation Strategy
190(6)
8.4 How Well Does This Work Cross-Linguistically?
196(11)
8.5 How Useful Are the Units?
207(12)
8.6 Closing Thoughts
219(8)
Part IV Social and Language Evolution
9 Social Evolution of Public Languages: Between Rousseau's Eden and Hobbes' Leviathan
227(29)
Anne Reboul
9.1 Introduction
227(1)
9.2 Is Language a Communication System in the Strong Sense?
228(5)
9.3 What is the Proper Social Account for the Exaptation of Language for Communication?
233(17)
9.4 Conclusion
250(6)
10 Genetic Biases in Language: Computer Models and Experimental Approaches
256(33)
Rick Janssen
Dan Dediu
10.1 Introduction
256(6)
10.2 Computer Models of Cultural Evolution
262(16)
10.3 Cultural Feedback
278(3)
10.4 Conclusion
281(8)
11 Transparency versus Processing Efficiency: A Case Study on German Declension
289(30)
Remi Van Trijp
11.1 Introduction
289(1)
11.2 German Declension: Not as Awful as It Seems
290(10)
11.3 Evaluating the Efficiency of Syncretism
300(14)
11.4 Discussion and Conclusions
314(5)
Index 319
Thierry Poibeau is Director of Research at Centre National de la Recherche Scientifique (CNRS), Paris and head of the LaTTiCE laboratory in Paris, France. His is also an affiliated lecturer at the Department of Theoretical and Applied Linguistics (DTAL) of the University of Cambridge. He works on natural language processing (NLP), in particular focusing on information extraction, question answering, semantic zoning, knowledge acquisition from text, and named entity tagging. Aline Villavicencio is a Reader at the Institute of Informatics, Universidade Federal do Rio Grande do Sul, Brazil, and is a fellow of CNPq (Brazil). Her research interests in natural language processing are in computational models of acquisition of linguistic information from data, distributional semantic models, multiword expression, and applications like text simplification and question answering.