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Symbols: An Evolutionary History from the Stone Age to the Future

ISBN-13: 9783031268083 / Angielski

Richard Sproat
Symbols: An Evolutionary History from the Stone Age to the Future Richard Sproat 9783031268083 Springer International Publishing AG - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Symbols: An Evolutionary History from the Stone Age to the Future

ISBN-13: 9783031268083 / Angielski

Richard Sproat
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For millennia humans have used visible marks to communicate information. Modern examples of conventional graphical symbols include written language, and non-linguistic symbol systems such as mathematical symbology or traffic signs. The latter kinds of symbols convey information without reference to language.This book presents the first systematic study of graphical symbol systems, including a history of graphical symbols from the Paleolithic onwards, a taxonomy of non-linguistic systems – systems that are not tied to spoken language – and a survey of more than 25 such systems. One important feature of many non-linguistic systems is that, as in written language, symbols may be combined into complex “messages” if the information the system represents is itself complex. To illustrate, the author presents an in-depth comparison of two systems that had very similar functions, but very different structure: European heraldry and Japanesekamon.Writing first appeared in Mesopotamia about 5,000 years ago and is believed to have evolved from a previous non-linguistic accounting system. The exact mechanism is unknown, but crucial was the discovery that symbols can represent the sounds of words, not just the meanings. The book presents a novel neurologically-inspired hypothesis that writing evolved in an institutional context in which symbols were “dictated”, thus driving an association between symbol and sound, and provides a computational simulation to support this hypothesis. The author further discusses some common fallacies about writing and non-linguistic systems, and how these relate to widely cited claims about statistical “evidence” for one or another system being writing. The book ends with some thoughts about the future of graphical symbol systems.The intended audience includes students, researchers, lecturers, professionals and scientists from fields like Natural Language Processing, Machine Learning, Archaeology and Semiotics, as well as general readers interested in language and/or writing systems and symbol systems.

For millennia humans have used visible marks to communicate information. Modern examples of conventional graphical symbols include written language, and non-linguistic symbol systems such as mathematical symbology or traffic signs. The latter kinds of symbols convey information without reference to language. 


This book presents the first systematic study of graphical symbol systems, including a history of graphical symbols from the Paleolithic onwards, a taxonomy of non-linguistic systems – systems that are not tied to spoken language – and a survey of more than 25 such systems. One important feature of many non-linguistic systems is that, as in written language, symbols may be combined into complex “messages” if the information the system represents is itself complex. To illustrate, the author presents an in-depth comparison of two systems that had very similar functions, but very different structure: European heraldry and Japanese kamon. 

Writing first appeared in Mesopotamia about 5,000 years ago and is believed to have evolved from a previous non-linguistic accounting system. The exact mechanism is unknown, but crucial was the discovery that symbols can represent the sounds of words, not just the meanings. The book presents a novel neurologically-inspired hypothesis that writing evolved in an institutional context in which symbols were “dictated”, thus driving an association between symbol and sound, and provides a computational simulation to support this hypothesis. The author further discusses some common fallacies about writing and non-linguistic systems, and how these relate to widely cited claims about statistical “evidence” for one or another system being writing. The book ends with some thoughts about the future of graphical symbol systems. 

The intended audience includes students, researchers, lecturers, professionals and scientists from fields like Natural Language Processing, Machine Learning, Archaeology and Semiotics, as well as general readers interested in language and/or writing systems and symbol systems.

Kategorie:
Informatyka, Bazy danych
Kategorie BISAC:
Computers > Speech & Audio Processing
Computers > Artificial Intelligence - General
Language Arts & Disciplines > Library & Information Science - General
Wydawca:
Springer International Publishing AG
Język:
Angielski
ISBN-13:
9783031268083

Preface

1 Introduction

1.1 What’s in a Symbol?

1.2 Syntax

1.3 What this book is about

2 Semiotics

2.1 Introduction

2.2 The Field of Semiotics

2.3 Iconicity

2.4 Syntax

2.5 Articulation

3 Taxonomy

3.1 Introduction

3.2 History

3.3 Preliminary Taxonomy

3.4 Examples of systems

3.5 Kamon/Heraldry

       3.5.1 Kamon

       3.5.2 British heraldry

       3.5.3 Structural Differences: Summary

3.A Symbol system survey (A detailed analysis of 26 symbol systems)

3.B Statistics of kamon

 

4 Writing Systems

4.1 Introduction

4.2 Writing

       4.2.1 Preliminaries

       4.2.2 Types of Writing Systems

       4.2.3 Blissymbolics

4.3 Limitations of writing

       4.3.1 Inclusiveness

       4.3.2 Graphocentrism

       4.3.3 Summary

4.4 Writing: A summary

5 Symbols in the Brain

5.1 Brain areas

5.2 Meaning in the brain

5.3 Reading in the brain

       5.3.1 The letterbox

       5.3.2 Summary: the evolution of the letterbox

5.4 Non-linguistic symbols in the brain

5.5 A Hypothesis

 

6 The Evolution of Writing

6.1 Evolution

6.2 A Hypothesis

6.3 Schools

 

7 Simulations

7.1 Prior work

7.2 Simulation

       7.2.1 Description of the model

       7.2.2 Simulation of evolution

       7.2.3 Summary and discussion

7.3 Pre-writing

7.4 Summary

7.A Details

       7.A.1 Data Generation

       7.A.2 Model

7.B Compounds

       7.B.1 Monosyllabic cases

       7.B.2 Sesquisyllabic cases

       7.B.3 Disyllabic cases

 

8 Misrepresentations

8.1 Introduction

8.2 What does it mean to say something "Looks like writing"?

8.3 Statistics

       8.3.1 Statistical analysis of the Indus Valley inscriptions

       8.3.2 More on structure in the Indus inscriptions

       8.3.3 Variations of distributions of symbols

8.4 Summary

 

9 The Future

9.1 The Dream of a Universal Written Language

9.2 Semasiography

9.3 The Prestige of Writing

9.4 Final Thoughts

Richard Sproat is a Senior Staff Research Scientist at Google, Japan, working on Deep Learning for applications in speech and language processing. He attended the University of California, San Diego and then MIT, where he received his Ph.D. in Linguistics in 1985. He has published widely in various areas of linguistics and computational linguistics, and he has a particular interest in writing systems and symbol systems. His prior relevant books in this area include A Computational Theory of Writing Systems (2000) and Language, Technology, and Society (2010). He has been invited as a speaker to various international venues related to writing and symbol systems, such as the "Signs of Writing" conference (Chicago, 2014; Beijing, 2015), and he was a keynote speaker at "Grapholinguistics in the 21st Century" (Paris, 2022). He was a contributor to the Routledge Handbook of the English Writing System (2016), wrote a chapter (with Amalia Gnanadesikan) on writing systems in the Oxford Bibliographies (2018), and contributed a chapter on writing systems to the Oxford History of Phonology (2022). He is on the editorial board of "Written Language and Literacy". 


For millennia humans have used visible marks to communicate information. Modern examples of conventional graphical symbols include written language, and non-linguistic symbol systems such as mathematical symbology or traffic signs. The latter kinds of symbols convey information without reference to language. ​


This book presents the first systematic study of graphical symbol systems, including a history of graphical symbols from the Paleolithic onwards, a taxonomy of non-linguistic systems – systems that are not tied to spoken language – and a survey of more than 25 such systems. One important feature of many non-linguistic systems is that, as in written language, symbols may be combined into complex “messages” if the information the system represents is itself complex. To illustrate, the author presents an in-depth comparison of two systems that had very similar functions, but very different structure: European heraldry and Japanese kamon. 

Writing first appeared in Mesopotamia about 5,000 years ago and is believed to have evolved from a previous non-linguistic accounting system. The exact mechanism is unknown, but crucial was the discovery that symbols can represent the sounds of words, not just the meanings. The book presents a novel neurologically-inspired hypothesis that writing evolved in an institutional context in which symbols were “dictated”, thus driving an association between symbol and sound, and provides a computational simulation to support this hypothesis. The author further discusses some common fallacies about writing and non-linguistic systems, and how these relate to widely cited claims about statistical “evidence” for one or another system being writing. The book ends with some thoughts about the future of graphical symbol systems. 

The intended audience includes students, researchers, lecturers, professionals and scientists from fields like Natural Language Processing, Machine Learning, Archaeology and Semiotics, as well as general readers interested in language and/or writing systems and symbol systems.

Richard Sproat is a Research Scientist at Google working on Deep Learning. He has a long-standing interest in writing systems and other graphical symbol systems.



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