Translation, Brains and the Computer, Bernard Scott
Автор: Scott Название: Translation, Brains and the Computer ISBN: 3319766287 ISBN-13(EAN): 9783319766287 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is about machine translation (MT) and the classic problems associated with this language technology. It examines the causes of these problems and, for linguistic, rule-based systems, attributes the cause to language’s ambiguity and complexity and their interplay in logic-driven processes. For non-linguistic, data-driven systems, the book attributes translation shortcomings to the very lack of linguistics. It then proposes a demonstrable way to relieve these drawbacks in the shape of a working translation model (Logos Model) that has taken its inspiration from key assumptions about psycholinguistic and neurolinguistic function. The book suggests that this brain-based mechanism is effective precisely because it bridges both linguistically driven and data-driven methodologies. It shows how simulation of this cerebral mechanism has freed this one MT model from the all-important, classic problem of complexity when coping with the ambiguities of language. Logos Model accomplishes this by a data-driven process that does not sacrifice linguistic knowledge, but that, like the brain, integrates linguistics within a data-driven process. As a consequence, the book suggests that the brain-like mechanism embedded in this model has the potential to contribute to further advances in machine translation in all its technological instantiations.
Автор: Lynne Bowker, Jairo Buitrago Ciro Название: Machine Translation and Global Research: Towards Improved Machine Translation Literacy in the Scholarly Community ISBN: 1787567222 ISBN-13(EAN): 9781787567221 Издательство: Emerald Рейтинг: Цена: 92140.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Lynne Bowker and Jairo Buitrago Ciro introduce the concept of machine translation literacy, a new kind of literacy for scholars and librarians in the digital age. This book is a must-read for researchers and information professionals eager to maximize the global reach and impact of any form of scholarly work.
With recent advances in natural language understanding techniques and far-field microphone arrays, natural language interfaces, such as voice assistants and chatbots, are emerging as a popular new way to interact with computers.
They have made their way out of the industry research labs and into the pockets, desktops, cars and living rooms of the general public. But although such interfaces recognize bits of natural language, and even voice input, they generally lack conversational competence, or the ability to engage in natural conversation. Today's platforms provide sophisticated tools for analyzing language and retrieving knowledge, but they fail to provide adequate support for modeling interaction. The user experience (UX) designer or software developer must figure out how a human conversation is organized, usually relying on commonsense rather than on formal knowledge. Fortunately, practitioners can rely on conversation science.
This book adapts formal knowledge from the field of Conversation Analysis (CA) to the design of natural language interfaces. It outlines the Natural Conversation Framework (NCF), developed at IBM Research, a systematic framework for designing interfaces that work like natural conversation. The NCF consists of four main components: 1) an interaction model of "expandable sequences," 2) a corresponding content format, 3) a pattern language with 100 generic UX patterns and 4) a navigation method of six basic user actions. The authors introduce UX designers to a new way of thinking about user experience design in the context of conversational interfaces, including a new vocabulary, new principles and new interaction patterns. User experience designers and graduate students in the HCI field as well as developers and conversation analysis students should find this book of interest.
Автор: Horacio Saggion Название: Automatic Text Simplification ISBN: 1627058680 ISBN-13(EAN): 9781627058681 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 51750.00 T Наличие на складе: Невозможна поставка. Описание: Presents research in text simplification, exploring key issues, including automatic readability assessment, lexical simplification, and syntactic simplification. It provides a detailed account of machine learning techniques currently used in simplification, describes full systems designed for specific languages and target audiences, and offers available resources for research and development.
Автор: Horacio Saggion Название: Automatic Text Simplification ISBN: 1681732149 ISBN-13(EAN): 9781681732145 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 72070.00 T Наличие на складе: Невозможна поставка. Описание: Automatic text simplification, a research topic which started 20 years ago, now has taken on a central role in natural language processing research. This book presents past and current research in text simplification, exploring key issues including automatic readability assessment, lexical simplification, and syntactic simplification.
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: Yunyao Li, Davood Rafiei Название: Natural Language Data Management and Interfaces ISBN: 1681734109 ISBN-13(EAN): 9781681734101 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 87780.00 T Наличие на складе: Невозможна поставка. Описание: The volume of natural language text data has been rapidly increasing over the past two decades, due to factors such as the growth of the Web, the low cost associated with publishing, and the progress on the digitization of printed texts. This growth combined with the proliferation of natural language systems for search and retrieving information provides tremendous opportunities for studying some of the areas where database systems and natural language processing systems overlap.This book explores two interrelated and important areas of overlap: (1) managing natural language data and (2) developing natural language interfaces to databases. It presents relevant concepts and research questions, state-of-the-art methods, related systems, and research opportunities and challenges covering both areas. Relevant topics discussed on natural language data management include data models, data sources, queries, storage and indexing, and transforming natural language text. Under natural language interfaces, it presents the anatomy of these interfaces to databases, the challenges related to query understanding and query translation, and relevant aspects of user interactions. Each of the challenges is covered in a systematic way: first starting with a quick overview of the topics, followed by a comprehensive view of recent techniques that have been proposed to address the challenge along with illustrative examples. It also reviews some notable systems in details in terms of how they address different challenges and their contributions. Finally, it discusses open challenges and opportunities for natural language management and interfaces.The goal of this book is to provide an introduction to the methods, problems, and solutions that are used in managing natural language data and building natural language interfaces to databases. It serves as a starting point for readers who are interested in pursuing additional work on these exciting topics in both academic and industrial environments.
Автор: Yunyao Li, Davood Rafiei Название: Natural Language Data Management and Interfaces ISBN: 1681734087 ISBN-13(EAN): 9781681734088 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 66530.00 T Наличие на складе: Невозможна поставка. Описание: The volume of natural language text data has been rapidly increasing over the past two decades, due to factors such as the growth of the Web, the low cost associated with publishing, and the progress on the digitization of printed texts. This growth combined with the proliferation of natural language systems for search and retrieving information provides tremendous opportunities for studying some of the areas where database systems and natural language processing systems overlap.This book explores two interrelated and important areas of overlap: (1) managing natural language data and (2) developing natural language interfaces to databases. It presents relevant concepts and research questions, state-of-the-art methods, related systems, and research opportunities and challenges covering both areas. Relevant topics discussed on natural language data management include data models, data sources, queries, storage and indexing, and transforming natural language text. Under natural language interfaces, it presents the anatomy of these interfaces to databases, the challenges related to query understanding and query translation, and relevant aspects of user interactions. Each of the challenges is covered in a systematic way: first starting with a quick overview of the topics, followed by a comprehensive view of recent techniques that have been proposed to address the challenge along with illustrative examples. It also reviews some notable systems in details in terms of how they address different challenges and their contributions. Finally, it discusses open challenges and opportunities for natural language management and interfaces.The goal of this book is to provide an introduction to the methods, problems, and solutions that are used in managing natural language data and building natural language interfaces to databases. It serves as a starting point for readers who are interested in pursuing additional work on these exciting topics in both academic and industrial environments.
With recent advances in natural language understanding techniques and far-field microphone arrays, natural language interfaces, such as voice assistants and chatbots, are emerging as a popular new way to interact with computers.
They have made their way out of the industry research labs and into the pockets, desktops, cars and living rooms of the general public. But although such interfaces recognize bits of natural language, and even voice input, they generally lack conversational competence, or the ability to engage in natural conversation. Today's platforms provide sophisticated tools for analyzing language and retrieving knowledge, but they fail to provide adequate support for modeling interaction. The user experience (UX) designer or software developer must figure out how a human conversation is organized, usually relying on commonsense rather than on formal knowledge. Fortunately, practitioners can rely on conversation science.
This book adapts formal knowledge from the field of Conversation Analysis (CA) to the design of natural language interfaces. It outlines the Natural Conversation Framework (NCF), developed at IBM Research, a systematic framework for designing interfaces that work like natural conversation. The NCF consists of four main components: 1) an interaction model of "expandable sequences," 2) a corresponding content format, 3) a pattern language with 100 generic UX patterns and 4) a navigation method of six basic user actions. The authors introduce UX designers to a new way of thinking about user experience design in the context of conversational interfaces, including a new vocabulary, new principles and new interaction patterns. User experience designers and graduate students in the HCI field as well as developers and conversation analysis students should find this book of interest.
Автор: Amitoj Singh, Munish Kumar, Virender Kadyan Название: Language and Speech Recognition for Human-Computer Interaction ISBN: 1799813908 ISBN-13(EAN): 9781799813903 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 136750.00 T Наличие на складе: Нет в наличии. Описание: In today's advancing society, the study of machine learning and artificial intelligence has been a popular area of research across the globe. One aspect of these technological developments is understanding the relationship between computers and human language. Helping computers understand natural linguistics has become a rapidly developing research area, as professionals need advanced techniques in document analysis and recognition methodologies. Understanding the fundamentals and applications of these processing skills is vital. Language and Speech Recognition for Human-Computer Interaction is a collection of innovative research on the methods and applications of natural language processing techniques (NLP) within computer science and programming. Along with discussing the current and future scope of NLP, this book highlights topics including handwriting recognition, acoustic analysis, and forensic document examination. This book is ideally designed for IT specialists, academicians, researchers, scholars, industry professionals, and students seeking current research on the advancement of computational linguistics.
Автор: Amitoj Singh, Munish Kumar, Virender Kadyan Название: Language and Speech Recognition for Human-Computer Interaction ISBN: 1799813894 ISBN-13(EAN): 9781799813897 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 212520.00 T Наличие на складе: Невозможна поставка. Описание: Presents research on the methods and applications of natural language processing techniques (NLP) within computer science and programming. Along with discussing the current and future scope of NLP, this book highlights topics including handwriting recognition, acoustic analysis, and forensic document examination.
Автор: Lucia Specia, Carolina Scarton, Gustavo Henrique Paetzold Название: Quality Estimation for Machine Translation ISBN: 1681733757 ISBN-13(EAN): 9781681733753 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 87780.00 T Наличие на складе: Невозможна поставка. Описание: Many applications within natural language processing involve performing text-to-text transformations, i.e., given a text in natural language as input, systems are required to produce a version of this text (e.g., a translation), also in natural language, as output. Automatically evaluating the output of such systems is an important component in developing text-to-text applications. Two approaches have been proposed for this problem: (i) to compare the system outputs against one or more reference outputs using string matching-based evaluation metrics and (ii) to build models based on human feedback to predict the quality of system outputs without reference texts. Despite their popularity, reference-based evaluation metrics are faced with the challenge that multiple good (and bad) quality outputs can be produced by text-to-text approaches for the same input. This variation is very hard to capture, even with multiple reference texts. In addition, reference-based metrics cannot be used in production (e.g., online machine translation systems), when systems are expected to produce outputs for any unseen input. In this book, we focus on the second set of metrics, so-called Quality Estimation (QE) metrics, where the goal is to provide an estimate on how good or reliable the texts produced by an application are without access to gold-standard outputs. QE enables different types of evaluation that can target different types of users and applications. Machine learning techniques are used to build QE models with various types of quality labels and explicit features or learnt representations, which can then predict the quality of unseen system outputs. This book describes the topic of QE for text-to-text applications, covering quality labels, features, algorithms, evaluation, uses, and state-of-the-art approaches. It focuses on machine translation as application, since this represents most of the QE work done to date. It also briefly describes QE for several other applications, including text simplification, text summarization, grammatical error correction, and natural language generation.
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