Ruslan Mitkov's highly successful Oxford Handbook of Computational Linguistics has been substantially revised and expanded in this second edition. Alongside updated accounts of the topics covered in the first edition, it includes 17 new chapters on subjects such as semantic role-labelling, text-to-speech synthesis, translation technology, opinion mining and sentiment analysis, and the application of Natural Language Processing in educational and biomedical contexts, among many others. The volume is divided into four parts that examine, respectively: the linguistic fundamentals of computational linguistics; the methods and resources used, such as statistical modelling, machine learning, and corpus annotation; key language processing tasks including text segmentation, anaphora resolution, and speech recognition; and the major applications of Natural Language Processing, from machine translation to author profiling. The book will be an essential reference for researchers and students in computational linguistics and Natural Language Processing, as well as those working in related industries. Preface List of abbreviations The contributors Part I. Linguistic Fundamentals 1. Phonology 2. Morphology 3. Lexis 4. Syntax 5. Semantics 6. Discourse 7. Pragmatics 8. Dialogue Part II. Computational Fundamentals: Methods and Resources 9. Mathematical Foundations, Formal Grammars and Languages 10. Finite-State Technology 11. Statistical Methods: Fundamentals 12. Statistical Models for Natural Language Processing 13. Machine Learning 14. Word Representation 15. Deep Learning 16. Similarity 17. Evaluation 18. Sublanguages and Controlled Languages 19. Lexicography 20. Corpora 21. Corpus Annotation 22. Ontologies Part III. Language Processing Tasks 23. Text Segmentation 24. Part-of-Speech Tagging 25. Parsing 26. Semantic Role Labelling 27. Word Sense Disambiguation 28. Computational Treatment of Multiword Expressions 29. Textual Entailment 30. Anaphora Resolution 31. Temporal Processing 32. Natural Language Generation 33. Speech Recognition 34. Text-to-Speech Synthesis Part IV. Natural Language Processing Applications 35. Machine Translation 36. Translation Technology 37. Information Retrieval 38. Information Extraction 39. Question Answering 40. Text Summarization 41. Term Extraction 42. Web Text Mining 43. Opinion Mining and Sentiment Analysis 44. Spoken Language Dialogue Systems 45. Multimodal Systems 46. Natural Language Processing for Educational Applications 47. Automated Writing Assistance 48. Text Simplification 49. Natural Language Processing for Biomedical Texts 50. Author Profiling and Related Applications 51. Recent Natural Language Processing Applications Ruslan Mitkov is Professor of Computational Linguistics and Language Engineering at the University of Wolverhampton, where he is also Director of the Research Institute for Information and Language Processing. He has worked in the fields of Natural Language Processing, computational linguistics, corpus linguistics, machine translation, translation technology, and related areas since the early 1980s. He is a Fellow of the Alexander von Humboldt Foundation, Germany; Marie Curie Fellow and Distinguished Visiting Professor at the University of Franche-Comté in Besançon, France; and Vice-Chair of the EC-funded programme 'Future and Emerging Technologies'.