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Empirical Methods in Natural Language Generation

Data-oriented Methods and Empirical Evaluation

  • Book
  • © 2010

Overview

Editors:
  1. Emiel Krahmer

    1. Faculty of Humanities, Department of Communication and Information Sciences (DCI), Tilburg University, Tilburg, The Netherlands

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  2. Mariët Theune

    1. Human Media Interaction (HMI), Department of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente, Enschede, The Netherlands

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5790)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: EACL 2009, ENLG 2009.

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Table of contents (16 chapters)

  1. Front Matter

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  2. Text-to-Text Generation

    1. Probabilistic Approaches for Modeling Text Structure and Their Application to Text-to-Text Generation

      • Regina Barzilay
      Pages 1-12

    2. Spanning Tree Approaches for Statistical Sentence Generation

      • Stephen Wan, Mark Dras, Robert Dale, Cécile Paris
      Pages 13-44

    3. On the Limits of Sentence Compression by Deletion

      • Erwin Marsi, Emiel Krahmer, Iris Hendrickx, Walter Daelemans
      Pages 45-66

  3. NLG in Interaction

    1. Learning Adaptive Referring Expression Generation Policies for Spoken Dialogue Systems

      • Srinivasan Janarthanam, Oliver Lemon
      Pages 67-84

    2. Modelling and Evaluation of Lexical and Syntactic Alignment with a Priming-Based Microplanner

      • Hendrik Buschmeier, Kirsten Bergmann, Stefan Kopp
      Pages 85-104

    3. Natural Language Generation as Planning under Uncertainty for Spoken Dialogue Systems

      • Verena Rieser, Oliver Lemon
      Pages 105-120

  4. Referring Expression Generation

    1. Generating Approximate Geographic Descriptions

      • Ross Turner, Somayajulu Sripada, Ehud Reiter
      Pages 121-140

    2. A Flexible Approach to Class-Based Ordering of Prenominal Modifiers

      • Margaret Mitchell
      Pages 141-162

    3. Attribute-Centric Referring Expression Generation

      • Robert Dale, Jette Viethen
      Pages 163-179

  5. Evaluation of NLG

    1. Assessing the Trade-Off between System Building Cost and Output Quality in Data-to-Text Generation

      • Anja Belz, Eric Kow
      Pages 180-200

    2. Human Evaluation of a German Surface Realisation Ranker

      • Aoife Cahill, Martin Forst
      Pages 201-221

    3. Structural Features for Predicting the Linguistic Quality of Text

      • Ani Nenkova, Jieun Chae, Annie Louis, Emily Pitler
      Pages 222-241

    4. Towards Empirical Evaluation of Affective Tactical NLG

      • Ielka van der Sluis, Chris Mellish
      Pages 242-263

  6. Shared Task Challenges for NLG

    1. Introducing Shared Tasks to NLG: The TUNA Shared Task Evaluation Challenges

      • Albert Gatt, Anja Belz
      Pages 264-293

    2. Generating Referring Expressions in Context: The GREC Task Evaluation Challenges

      • Anja Belz, Eric Kow, Jette Viethen, Albert Gatt
      Pages 294-327

    3. The First Challenge on Generating Instructions in Virtual Environments

      • Alexander Koller, Kristina Striegnitz, Donna Byron, Justine Cassell, Robert Dale, Johanna Moore et al.
      Pages 328-352

  7. Back Matter

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Keywords

About this book

Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research.

Editors and Affiliations

  • Faculty of Humanities, Department of Communication and Information Sciences (DCI), Tilburg University, Tilburg, The Netherlands

    Emiel Krahmer

  • Human Media Interaction (HMI), Department of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente, Enschede, The Netherlands

    Mariët Theune

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