New Language Technologies and Linguistic Research


Book Description

This book is a collection of the papers presented and discussed at the 11th Corpus Linguistics Symposium (ELC 2012), held at the Instituto de Ciências Matemáticas e de Computação (Institute of Mathematics and Computer Science) of the University of São Paulo, at São Carlos, Brazil. The sessions addressed the following six topics: Corpus Linguistics and Language Description; Translation, Terminology and Corpora; Spoken Language and Corpora; Natural Language Processing and Corpora; Corpus Annotation; and Corpora and Multiple Documents. These unique studies will inspire readers with an interest in Linguistics, and will provide motivation for conducting further research in the interdisciplinary area of Language Technologies and Linguistic Research.




Introducing Linguistic Research


Book Description

Over the past decade, conducting empirical research in linguistics has become increasingly popular. The first of its kind, this book provides an engaging and practical introduction to this exciting versatile field, providing a comprehensive overview of research aspects in general, and covering a broad range of subdiscipline-specific methodological approaches. Subfields covered include language documentation and descriptive linguistics, language typology, corpus linguistics, sociolinguistics and anthropological linguistics, cognitive linguistics and psycholinguistics, and neurolinguistics. The book reflects on the strengths and weaknesses of each single approach and on how they interact with one-another across the study of language in its many diverse facets. It also includes exercises, example student projects and recommendations for further reading, along with additional online teaching materials. Providing hands-on experience, and written in an engaging and accessible style, this unique and comprehensive guide will give students the inspiration they need to develop their own research projects in empirical linguistics.




Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences


Book Description

Making diverse data in linguistics and the language sciences open, distributed, and accessible: perspectives from language/language acquistiion researchers and technical LOD (linked open data) researchers. This volume examines the challenges inherent in making diverse data in linguistics and the language sciences open, distributed, integrated, and accessible, thus fostering wide data sharing and collaboration. It is unique in integrating the perspectives of language researchers and technical LOD (linked open data) researchers. Reporting on both active research needs in the field of language acquisition and technical advances in the development of data interoperability, the book demonstrates the advantages of an international infrastructure for scholarship in the field of language sciences. With contributions by researchers who produce complex data content and scholars involved in both the technology and the conceptual foundations of LLOD (linguistics linked open data), the book focuses on the area of language acquisition because it involves complex and diverse data sets, cross-linguistic analyses, and urgent collaborative research. The contributors discuss a variety of research methods, resources, and infrastructures. Contributors Isabelle Barrière, Nan Bernstein Ratner, Steven Bird, Maria Blume, Ted Caldwell, Christian Chiarcos, Cristina Dye, Suzanne Flynn, Claire Foley, Nancy Ide, Carissa Kang, D. Terence Langendoen, Barbara Lust, Brian MacWhinney, Jonathan Masci, Steven Moran, Antonio Pareja-Lora, Jim Reidy, Oya Y. Rieger, Gary F. Simons, Thorsten Trippel, Kara Warburton, Sue Ellen Wright, Claus Zinn




Linguistic Issues in Language Technology Vol 9


Book Description

Linguistic Issues in Language Technology (LiLT) is an open-access journal that focuses on the relationships between linguistic insights and language technology. In conjunction with machine learning and statistical techniques, deeper and more sophisticated models of language and speech are needed to make significant progress in both existing and newly emerging areas of computational language analysis. The vast quantity of electronically accessible natural language data (text and speech, annotated and unannotated, formal and informal) provides unprecedented opportunities for data-intensive analysis of linguistic phenomena, which can in turn enrich computational methods. Taking an eclectic view on methodology, LiLT provides a forum for this work. In this volume, contributors offer new perspectives on semantic representations for textual inference.




Language Development in the Digital Age


Book Description

The digital age is changing our children’s lives and childhood dramatically. New technologies transform the way people interact with each other, the way stories are shared and distributed, and the way reality is presented and perceived. Parents experience that toddlers can handle tablets and apps with a level of sophistication the children’s grandparents can only envy. The question of how the ecology of the child affects the acquisition of competencies and skills has been approached from different angles in different disciplines. In linguistics, psychology and neuroscience, the central question addressed concerns the specific role of exposure to language. Two influential types of theory have been proposed. On one view the capacity to learn language is hard-wired in the human brain: linguistic input is merely a trigger for language to develop. On an alternative view, language acquisition depends on the linguistic environment of the child, and specifically on language input provided through child-adult communication and interaction. The latter view further specifies that factors in situated interaction are crucial for language learning to take place. In the fields of information technology, artificial intelligence and robotics a current theme is to create robots that develop, as children do, and to establish how embodiment and interaction support language learning in these machines. In the field of human-machine interaction, research is investigating whether using a physical robot, rather than a virtual agent or a computer-based video, has a positive effect on language development. The Research Topic will address the following issues: - What are the methodological challenges faced by research on language acquisition in the digital age? - How should traditional theories and models of language acquisition be revised to account for the multimodal and multichannel nature of language learning in the digital age? - How should existing and future technologies be developed and transformed so as to be most beneficial for child language learning and cognition? - Can new technologies be tailored to support child growth, and most importantly, can they be designed in order to enhance specifically vulnerable children’s language learning environment and opportunities? - What kind of learning mechanisms are involved? - How can artificial intelligence and robotics technologies, as robot tutors, support language development? These questions and issues can only be addressed by means of an interdisciplinary approach that aims at developing new methods of data collection and analysis in cross-sectional and longitudinal perspectives. We welcome contributions addressing these questions from an interdisciplinary perspective both theoretically and empirically.




Linguistics for the Age of AI


Book Description

A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.




Language Teaching in the Linguistic Landscape


Book Description

This book builds upon the growing field of Linguistic Landscape in order to demonstrate the power of a spatialized approach to language, culture, and literacy education as it opens classrooms and cultivates new competencies. The chapters develop major themes, including re-imagining language curricula, language classrooms, and schoolscapes in dialogue with the heteroglossic discourses of the local; developing L2 learners’ symbolic, translingual competencies through engagement with situated, multimodal texts; fostering critical social awareness through language study in the linguistic landscape; expanding opportunities for situated L2 reading and writing; and cultivating language students’ capacities for engaged scholarship and research in out-of-class contexts. By exploring the pedagogical possibilities of place-based approaches to literacy development, this volume contributes to the reimagining of language education through the linguistic landscape.




Technology-Enhanced Learning and Linguistic Diversity


Book Description

Drawing on research and hands-on experience, this book includes contributions which draw on linguistic research on 2nd and 3rd language acquisition, as well as case studies of specific challenges in teaching content courses in various disciplines, to offer a roadmap of how educators might facilitate the learning of their bilingual student cohort.




AI in Language Teaching, Learning, and Assessment


Book Description

The introduction of Artificial Intelligence (AI) has ignited a fervent academic discourse. AI's role is as both a powerful ally and a potential adversary in education. For instance, ChatGPT is a generative AI which mimics human conversation with impressive precision. Its capabilities span the educational spectrum, from answering questions and generating essays to composing music and coding. Yet, as with any innovation, its advent has sparked a spirited academic dialogue. AI in Language Teaching, Learning, and Assessment seeks to address these concerns with rigor and thoughtfulness. It explores the undeniable drawbacks of AI in language education and offers strategic insights into their prevention. It scrutinizes the resources and safeguards required to ensure the ethical and secure integration of AI in academic settings. This book lays out the multifaceted benefits of incorporating AI into language teaching, learning, and assessment. Its chapters dissect the transformative impact of AI on pedagogy, teaching materials, assessment methodologies, applied linguistics, and the broader landscape of language education development. This book is a valuable resource for language learners, educators, researchers, and scholars alike. It beckons to those who are keen on exploring and implementing AI in education, as well as AI developers and experts seeking to bridge the chasm between technology and language education.




Artificial Intelligence in China


Book Description

This book brings together papers presented at the 4th International Conference on Artificial Intelligence in China (ChinaAI), Changbaishan, China, on July 23-24, 2022, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics covering all topics in Artificial Intelligence with new development in China, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD, DOE, etc).