| Description |
1 online resource |
| Contents |
Intro -- Preface -- From ELIZA to ChatGPT -- Pedagogical Objectives -- For Whom Is This Book Written, and How To Read It -- Acknowledgments -- Contents -- Chapter 1 Introduction -- 1.1 What Is Language in the First Place? -- 1.2 Principles of Linguistics and of Language -- 1.2.1 Signifier and Signified -- 1.2.2 Opposition, Etics and Emics -- 1.2.3 Paradigmatic Axis and Syntagmatic Axis -- 1.2.4 Compositionality -- 1.2.5 Modalities of Language -- 1.2.6 Functions of Language -- 1.2.7 Sapir-Whorf and the Eskimo Vocabulary Hoax -- 1.3 A Terminological Issue: Data-Information-Knowledge |
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1.4 Notations -- 1.5 Exercises and Hints -- 1.6 Resources and Errata -- References -- Part I Linguistics -- Chapter 2 Phonetics/Phonology -- 2.1 Articulatory Phonetics -- 2.1.1 (Pulmonic) Consonants -- 2.1.2 Vowels -- 2.2 Acoustic Phonetics -- 2.3 From Phonetics to Phonemics -- 2.3.1 Features -- 2.3.2 Phonemes -- 2.4 Phonological Rules -- 2.4.1 Underlying Representation -- 2.5 Suprasegmental Aspects -- 2.5.1 Syllables -- 2.5.2 Stress and Foot -- 2.5.3 Mora -- 2.5.4 Tone -- 2.5.5 Prosody -- 2.6 iPA Phonetics, an App for Learning Phonetics -- 2.7 Psycholinguistic Aspects, Perceptual Phonetics |
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2.8 Further Reading -- 2.8.1 Literature -- 2.8.2 LATEX -- 2.8.3 Science Fiction -- 2.9 Exercises -- Exercise 1-1: English Accents -- Exercise 1-2: Phonotactics of English -- Exercise 1-3: Tonotactics of Vietnamese -- Exercise 1-4: Classification of Voice Files -- References -- Chapter 3 Graphetics/Graphemics -- 3.1 Graphetics -- 3.1.1 Descriptive Graphetics -- 3.1.1.1 Cheirographetics, or the Study of Handwriting -- 3.1.1.2 Typographetics -- 3.1.1.3 Descriptive Levels -- 3.1.1.4 Kerning and Ligatures -- 3.1.1.5 Typographetic Functions and Connotations -- 3.2 Graphemics |
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3.2.1 Writing Systems and Scripts -- 3.2.2 Pictography, Emoji -- 3.2.3 Orthography -- 3.2.4 Hyphenation and Non-breakability -- 3.2.5 Graphemic Gender-neutral Methods -- 3.2.6 Sinographemics -- 3.3 Psycholinguistic Aspects of Reading -- 3.4 Further Reading -- 3.4.1 Literature -- 3.4.2 LATEX -- 3.4.3 Science Fiction -- 3.5 Exercises -- Exercise 2-1: Evaluating ALA-LC Transcriptions of Arabic and Greek -- Exercise 2-2: Graphotactics of English -- Exercise 2-3: Greek Car License Plate and Signs -- Exercise 2-4: Predictability of New Sinograms -- Exercise 2-5: Exotype Classification -- References |
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Chapter 4 Morphemes, Words, Terms -- 4.1 Words -- 4.2 Lexemes -- 4.3 Parts of Speech -- 4.4 Morphemes -- 4.5 Inflection -- 4.6 Derivation -- 4.7 Compounding -- 4.8 Astonishing Morphologies: Semitic Languages and Lojban -- 4.8.1 Semitic Languages -- 4.8.2 Lojban -- 4.9 Terms and Collocations -- 4.10 Psycholinguistic Aspects -- Finding Words -- Building Words -- Phonological Encoding -- Keylogs -- 4.11 Further Reading -- 4.11.1 Literature -- 4.11.2 Science Fiction -- Orwell's Newspeak -- Time Travel and Verb Morphology -- The Golem -- 4.12 Exercises |
| Summary |
Natural Language Processing is the branch of Artificial Intelligence involving language, be it in spoken or written modality. Teaching Natural Language Processing (NLP) is difficult because of its inherent connections with other disciplines, such as Linguistics, Cognitive Science, Knowledge Representation, Machine Learning, Data Science, and its latest avatar: Deep Learning. Most introductory NLP books favor one of these disciplines at the expense of others. Based on a course on Natural Language Processing taught by the author at IMT Atlantique for over a decade, this textbook considers three points of view corresponding to three different disciplines, while granting equal importance to each of them. As such, the book provides a thorough introduction to the topic following three main threads: the fundamental notions of Linguistics, symbolic Artificial Intelligence methods (based on knowledge representation languages), and statistical methods (involving both legacy machine learning and deep learning tools). Complementary to this introductory text is teaching material, such as exercises and labs with hints and expected results. Complete solutions with Python code are provided for educators on the SpringerLink webpage of the book. This material can serve for classes given to undergraduate and graduate students, or for researchers, instructors, and professionals in computer science or linguistics who wish to acquire or improve their knowledge in the field. The book is suitable and warmly recommended for self-study |
| Notes |
Description based on online resource; title from digital title page (viewed on April 18, 2024) |
| Subject |
Natural language processing (Computer science)
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| Form |
Electronic book
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| ISBN |
9783031272264 |
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3031272269 |
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