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Beschreibung
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.
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.
Über den Autor
Brian Roark is a research scientist at Google. He received his PhD from Brown University in 2001, and joined the Speech Algorithms Department of AT&T Labs – Research, where his research focused on syntactic processing techniques and statistical language modeling approaches. In 2004, he joined the Center for Spoken Language Understanding of the Oregon Health & Science University, where he expanded his research program to include biomedical applications such as augmentative and alternative communication, brain computer interfaces and automated neuropsychological assessment. He was PI on numerous NSF, NIH and DARPA grants, and published more than 50 papers in journals and major conferences, receiving several best paper awards. He joined Google as a research scientist in 2013, where he continues to research problems in speech, NLP and text entry on mobile devices.

Richard Sproat is a research scientist at [...], working on artificial intelligence in language processing, agentic systems and image understanding. He received his PhD in Linguistics from MIT in 1985. He has published in various areas of linguistics and computational linguistics, and he has a particular interest in writing and symbol systems. His prior relevant books in this area include A Computational Theory of Writing Systems (2000), Language, Technology, and Society (2010) and Symbols: An Evolutionary History from the Stone Age to the Future (2023). He was an invited speaker at various international venues, such as the "Signs of Writing" conference (Chicago, 2014; Beijing, 2015), and a keynote speaker at "Grapholinguistics in the 21st Century" (Paris, 2022). Contributor to the Routledge Handbook of the English Writing System (2016), he wrote a chapter (with Amalia Gnanadesikan) on writing systems in the Oxford Bibliographies (2018), and a chapter on writing systems to the Oxford History of Phonology (2022). He is on the editorial board of Written Language and Literacy.

Su-Youn Yoon is a manager of the automated scoring team at EduLab, Inc., Japan. She received her
PhD in Linguistics from University of Illinois at Urbana Champaign in 2009 and joined the NLP and
Speech group at Educational Testing Service (ETS). Her early research centered on scoring non-native speakers’ oral proficiency. In the automated speech scoring field, grammar and vocabulary scoring presented notable challenges. Yoon, as one of the pioneering researchers, addressed this by leveraging shallow parsing and vocabulary profiling. Yoon has actively contributed to the improvement of the assessment landscape, particularly in test security. Her research delved into potential risks associated with automated scoring systems, such as test takers’ attempts to manipulate the system. In 2019, she left ETS and joined EduLab, Inc, expanding her focus on automated learning solutions for non-native writers. She is developing an automated system to identify priority issues of language learners, offering personalized and actionable feedback. She has published more than 50 papers in journals and major conferences, and authored chapters in Automated Speaking Assessment: Using Language Technologies to Score Spontaneous Speech, published by Routledge (2020).
Inhaltsverzeichnis
1. Introduction.- 2. Semiotics.- 3. Taxonomy.- 4. Writing Systems.- 5. Symbols in the Brain.- 6. The Evolution of Writing.- 7. Simulations.- 8. Misrepresentations.- 9. The Future.
Details
Erscheinungsjahr: 2023
Genre: Informatik, Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: xiii
235 S.
34 s/w Illustr.
57 farbige Illustr.
235 p. 91 illus.
57 illus. in color.
ISBN-13: 9783031268083
ISBN-10: 3031268083
Sprache: Englisch
Einband: Gebunden
Autor: Sproat, Richard
Hersteller: Springer
Springer International Publishing AG
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 241 x 160 x 20 mm
Von/Mit: Richard Sproat
Erscheinungsdatum: 01.08.2023
Gewicht: 0,547 kg
Artikel-ID: 126466508

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