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    • Publisher:
      Cambridge University Press
      Publication date:
      30 November 2017
      25 January 2018
      ISBN:
      9781316676974
      9781107162228
      Dimensions:
      (228 x 152 mm)
      Weight & Pages:
      0.6kg, 336 Pages
      Dimensions:
      Weight & Pages:
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    Book description

    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.

    Reviews

    '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 Source: Choice

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    Contents

    • Frontmatter
      pp i-iv
    • Contents
      pp v-viii
    • Figures
      pp ix-x
    • Tables
      pp xi-xiv
    • Contributors
      pp xv-xvi
    • Part I - About This Book
      pp 1-2
    • 1 - Introduction: Cognitive Issues in Natural Language Processing
      pp 3-24
      • By Thierry Poibeau, Lattice laboratory, CNRS and, Ecole Normale Supérieure and Université Sorbonne nouvelle, France, Aline Villavicencio, Institute of Informatics, Federal University of Rio Grande do Sul, Brazil, and School of Computer Science and Electronic Engineering, University of Essex, UK
    • Part II - Models of Neural and Cognitive Processing
      pp 25-26
    • 2 - Light and Deep Parsing: A Cognitive Model of Sentence Processing
      pp 27-52
      • By Philippe Blache, Laboratoire Parole et Langage, CNRS & Aix-Marseille Université, France
    • 3 - Decoding Language from the Brain
      pp 53-80
      • By Brian Murphy, Centre for Data Science and Scalable Computing, Queen's University, Belfast, Northern Ireland, Leila Wehbe, Helen Wills Neuroscience Institute, University of California, Berkeley, USA, Alona Fyshe, Department of Computer Science, University of Victoria, Canada
    • 4 - Graph Theory Applied to Speech: Insights on Cognitive Deficit Diagnosis and Dream Research
      pp 81-98
    • Part III - Data Driven Models
      pp 99-100
    • 5 - Putting Linguistics Back into Computational Linguistics
      pp 101-117
      • By Martin Kay, Department of Linguistics, Stanford University, USA
    • 6 - A Distributional Model of Verb-Specific Semantic Roles Inferences
      pp 118-158
      • By Gianluca E. Lebani, Department of Philology, Literature, and Linguistics, University of Pisa, Italy, Alessandro Lenci, Department of Philology, Literature, and Linguistics, University of Pisa, Italy
    • 7 - Native Language Identification on EFCAMDAT
      pp 159-184
      • By Xiao Jiang, Computer Laboratory, University of Cambridge, UK, Yan Huang, Department of Theoretical and Applied Linguistics, University of Cambridge, UK, Yufan Guo, IBM Research, USA, Jeroen Geertzen, Department of Theoretical and Applied Linguistics, University of Cambridge, UK, Theodora Alexopoulou, Department of Theoretical and Applied Linguistics, University of Cambridge, UK, Lin Sun, Greedy Intelligence, China, Anna Korhonen, Department of Theoretical and Applied Linguistics, University of Cambridge, UK
    • 8 - Evaluating Language Acquisition Models: A Utility-Based Look at Bayesian Segmentation
      pp 185-224
      • By Lisa Pearl, Departments of Linguistics and Cognitive Sciences, University of California, Irvine, USA, Lawrence Phillips, Department of Cognitive Sciences, University of California, Irvine, USA
    • Part IV - Social and Language Evolution
      pp 225-226
    • 9 - Social Evolution of Public Languages: Between Rousseau's Eden and Hobbes’ Leviathan
      pp 227-255
      • By Anne Reboul, Institute for Cognitive Sciences-Marc Jeannerod, CNRS UMR 5304, University of Lyon, France
    • 10 - Genetic Biases in Language: Computer Models and Experimental Approaches
      pp 256-288
      • By Rick Janssen, Language and Genetics Department, Max Planck Institute for Psycholinguistics, The Netherlands, Dan Dediu, Language and Genetics Department,Max Planck Institute for Psycholinguistics, The Netherlands
    • 11 - Transparency versus Processing Efficiency: A Case Study on German Declension
      pp 289-318
    • Index
      pp 319-322

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