Probabilistic approaches to linguistic theory:
"During the last two decades, computational linguists, in concert with other researchers in AI, have turned to machine learning and statistical techniques to capture features of natural language and aspects of the learning process that are not easily accommodated in classical algebraic framewor...
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| Other Authors: | , , , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Stanford, California
CSLI, Center for the Study of Language and Information
[2022]
|
| Subjects: | |
| Summary: | "During the last two decades, computational linguists, in concert with other researchers in AI, have turned to machine learning and statistical techniques to capture features of natural language and aspects of the learning process that are not easily accommodated in classical algebraic frameworks. These developments are producing a revolution in linguistics in which traditional symbolic systems are giving way to probabilistic and deep learning approaches. This collection features articles that provide background to these approaches, and their application in syntax, semantics, pragmatics, morphology, psycholinguistics, neurolinguistics, and dialogue modeling. Each chapter provides a self-contained introduction to the topic that it covers, making this volume accessible to graduate students and researchers in linguistics, NLP, AI, and cognitive science"-- |
| Physical Description: | x, 453 Seiten Illustrationen 23 cm |
| ISBN: | 9781684000791 |
Staff View
MARC
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| 245 | 1 | 0 | |a Probabilistic approaches to linguistic theory |c edited by Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, Aleksandre Maskharashvili |
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| 505 | 8 | |a Introduction -- 1. Computational Morphology / Christo Kirov and Richard Sproat -- 2. Something Old, Something New : Grammar-based CCG Parsing with Transformer Models / Stephen Clark -- 3. Probabilistic Lexical Semantics: From Gaussian Embeddings to Bernoulli Fields / Guy Emerson -- 4. The origins of vagueness / Peter Sutton -- 5. Bayesian Inference Semantics for Natural Language / Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin and Aleksandre Maskharashvili -- 6. Probabilistic pragmatics : a dialogical perspective / Bill Noble, Vladislav Maraev, and Ellen Breitholtz -- 7. Neuro-computation for language processing / Vidya Somashekarappa -- 8. Learning Language Games Probabilistically : From Crying to Compositionality / Robin Cooper, Jonathan Ginzburg and Staffan Larsson -- 9. Distributional Semantics for Situated Spatial Language? Functional, Geometric and Perceptual Perspectives / John D. Kelleher and Simon Dobnik -- 10. Action coordination and learning in dialogue / Arash Eshghi, Christine Howes, and Eleni Gregoromichelaki -- 11. Reanalysis, probability, and the faculty of language / Asad B. Sayeed -- Contributors -- Glossary | |
| 520 | 3 | |a "During the last two decades, computational linguists, in concert with other researchers in AI, have turned to machine learning and statistical techniques to capture features of natural language and aspects of the learning process that are not easily accommodated in classical algebraic frameworks. These developments are producing a revolution in linguistics in which traditional symbolic systems are giving way to probabilistic and deep learning approaches. This collection features articles that provide background to these approaches, and their application in syntax, semantics, pragmatics, morphology, psycholinguistics, neurolinguistics, and dialogue modeling. Each chapter provides a self-contained introduction to the topic that it covers, making this volume accessible to graduate students and researchers in linguistics, NLP, AI, and cognitive science"-- | |
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Record in the Search Index
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| author2 | Bernardy, Jean-Philippe 1978- Blanck, Rasmus 1982- Chatzikyriakidis, Stergios Lappin, Shalom Maskharashvili, Aleksandre |
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| building | Verbundindex |
| bvnumber | BV048892714 |
| contents | Introduction -- 1. Computational Morphology / Christo Kirov and Richard Sproat -- 2. Something Old, Something New : Grammar-based CCG Parsing with Transformer Models / Stephen Clark -- 3. Probabilistic Lexical Semantics: From Gaussian Embeddings to Bernoulli Fields / Guy Emerson -- 4. The origins of vagueness / Peter Sutton -- 5. Bayesian Inference Semantics for Natural Language / Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin and Aleksandre Maskharashvili -- 6. Probabilistic pragmatics : a dialogical perspective / Bill Noble, Vladislav Maraev, and Ellen Breitholtz -- 7. Neuro-computation for language processing / Vidya Somashekarappa -- 8. Learning Language Games Probabilistically : From Crying to Compositionality / Robin Cooper, Jonathan Ginzburg and Staffan Larsson -- 9. Distributional Semantics for Situated Spatial Language? Functional, Geometric and Perceptual Perspectives / John D. Kelleher and Simon Dobnik -- 10. Action coordination and learning in dialogue / Arash Eshghi, Christine Howes, and Eleni Gregoromichelaki -- 11. Reanalysis, probability, and the faculty of language / Asad B. Sayeed -- Contributors -- Glossary |
| ctrlnum | (OCoLC)1392140725 (DE-599)BVBBV048892714 |
| format | Book |
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| id | DE-604.BV048892714 |
| illustrated | Illustrated |
| index_date | 2024-07-03T21:48:47Z |
| indexdate | 2025-02-13T09:00:48Z |
| institution | BVB |
| isbn | 9781684000791 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034157274 |
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| owner_facet | DE-12 |
| physical | x, 453 Seiten Illustrationen 23 cm |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | CSLI, Center for the Study of Language and Information |
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| spelling | Probabilistic approaches to linguistic theory edited by Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, Aleksandre Maskharashvili Stanford, California CSLI, Center for the Study of Language and Information [2022] x, 453 Seiten Illustrationen 23 cm txt rdacontent n rdamedia nc rdacarrier Introduction -- 1. Computational Morphology / Christo Kirov and Richard Sproat -- 2. Something Old, Something New : Grammar-based CCG Parsing with Transformer Models / Stephen Clark -- 3. Probabilistic Lexical Semantics: From Gaussian Embeddings to Bernoulli Fields / Guy Emerson -- 4. The origins of vagueness / Peter Sutton -- 5. Bayesian Inference Semantics for Natural Language / Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin and Aleksandre Maskharashvili -- 6. Probabilistic pragmatics : a dialogical perspective / Bill Noble, Vladislav Maraev, and Ellen Breitholtz -- 7. Neuro-computation for language processing / Vidya Somashekarappa -- 8. Learning Language Games Probabilistically : From Crying to Compositionality / Robin Cooper, Jonathan Ginzburg and Staffan Larsson -- 9. Distributional Semantics for Situated Spatial Language? Functional, Geometric and Perceptual Perspectives / John D. Kelleher and Simon Dobnik -- 10. Action coordination and learning in dialogue / Arash Eshghi, Christine Howes, and Eleni Gregoromichelaki -- 11. Reanalysis, probability, and the faculty of language / Asad B. Sayeed -- Contributors -- Glossary "During the last two decades, computational linguists, in concert with other researchers in AI, have turned to machine learning and statistical techniques to capture features of natural language and aspects of the learning process that are not easily accommodated in classical algebraic frameworks. These developments are producing a revolution in linguistics in which traditional symbolic systems are giving way to probabilistic and deep learning approaches. This collection features articles that provide background to these approaches, and their application in syntax, semantics, pragmatics, morphology, psycholinguistics, neurolinguistics, and dialogue modeling. Each chapter provides a self-contained introduction to the topic that it covers, making this volume accessible to graduate students and researchers in linguistics, NLP, AI, and cognitive science"-- Deep Learning (DE-588)1135597375 gnd rswk-swf Sprachverarbeitung (DE-588)4116579-2 gnd rswk-swf Computerlinguistik (DE-588)4035843-4 gnd rswk-swf Computational linguistics Natural language processing (Computer science) Deep learning (Machine learning) Computerlinguistik (DE-588)4035843-4 s Sprachverarbeitung (DE-588)4116579-2 s Deep Learning (DE-588)1135597375 s DE-604 Bernardy, Jean-Philippe 1978- (DE-588)1281734942 edt Blanck, Rasmus 1982- (DE-588)1256802832 edt Chatzikyriakidis, Stergios (DE-588)1137069740 edt Lappin, Shalom (DE-588)1077224141 edt Maskharashvili, Aleksandre edt Erscheint auch als Online-Ausgabe 978-1-68400-080-7 |
| spellingShingle | Probabilistic approaches to linguistic theory Introduction -- 1. Computational Morphology / Christo Kirov and Richard Sproat -- 2. Something Old, Something New : Grammar-based CCG Parsing with Transformer Models / Stephen Clark -- 3. Probabilistic Lexical Semantics: From Gaussian Embeddings to Bernoulli Fields / Guy Emerson -- 4. The origins of vagueness / Peter Sutton -- 5. Bayesian Inference Semantics for Natural Language / Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin and Aleksandre Maskharashvili -- 6. Probabilistic pragmatics : a dialogical perspective / Bill Noble, Vladislav Maraev, and Ellen Breitholtz -- 7. Neuro-computation for language processing / Vidya Somashekarappa -- 8. Learning Language Games Probabilistically : From Crying to Compositionality / Robin Cooper, Jonathan Ginzburg and Staffan Larsson -- 9. Distributional Semantics for Situated Spatial Language? Functional, Geometric and Perceptual Perspectives / John D. Kelleher and Simon Dobnik -- 10. Action coordination and learning in dialogue / Arash Eshghi, Christine Howes, and Eleni Gregoromichelaki -- 11. Reanalysis, probability, and the faculty of language / Asad B. Sayeed -- Contributors -- Glossary Deep Learning (DE-588)1135597375 gnd Sprachverarbeitung (DE-588)4116579-2 gnd Computerlinguistik (DE-588)4035843-4 gnd |
| subject_GND | (DE-588)1135597375 (DE-588)4116579-2 (DE-588)4035843-4 |
| title | Probabilistic approaches to linguistic theory |
| title_auth | Probabilistic approaches to linguistic theory |
| title_exact_search | Probabilistic approaches to linguistic theory |
| title_exact_search_txtP | Probabilistic approaches to linguistic theory |
| title_full | Probabilistic approaches to linguistic theory edited by Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, Aleksandre Maskharashvili |
| title_fullStr | Probabilistic approaches to linguistic theory edited by Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, Aleksandre Maskharashvili |
| title_full_unstemmed | Probabilistic approaches to linguistic theory edited by Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, Aleksandre Maskharashvili |
| title_short | Probabilistic approaches to linguistic theory |
| title_sort | probabilistic approaches to linguistic theory |
| topic | Deep Learning (DE-588)1135597375 gnd Sprachverarbeitung (DE-588)4116579-2 gnd Computerlinguistik (DE-588)4035843-4 gnd |
| topic_facet | Deep Learning Sprachverarbeitung Computerlinguistik |
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