Translation tools and technologies, Rothwell, Andrew Moorkens, Joss Fernandez-parra, M

Автор: Rothwell, Andrew Moorkens, Joss Fernandez-parra, Maria Drugan, Joanna Austermuehl, Frank
Название: Translation tools and technologies
ISBN: 0367750333 ISBN-13(EAN): 9780367750336
Издательство: Taylor&Francis
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Цена: 122490.00 T
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Описание: Demystifying the workings of Computer-Assisted Translation (CAT) and Machine Translation (MT) technologies, this book offers clear step-by-step guidance on how to choose suitable tools (free or commercial) for the task in hand and quickly get up to speed with them, using examples from a wide range of languages.

Автор: Goldberg Yoav
Название: Neural Network Methods in Natural Language Processing
ISBN: 1627052984 ISBN-13(EAN): 9781627052986
Издательство: Mare Nostrum (Eurospan)
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Цена: 76690.00 T
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Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

Автор: Sch?fer, R. and Bildhauer, F.
Название: Web Corpus Construction. Synthesis Lectures on Human Language Technologies
ISBN: 1608459837 ISBN-13(EAN): 9781608459834
Издательство: Turpin
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Цена: 30790.00 T
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Описание: The World Wide Web constitutes the largest existing source of texts written in a great variety of languages. A feasible and sound way of exploiting this data for linguistic research is to compile a static corpus for a given language. There are several adavantages of this approach: (i) Working with such corpora obviates the problems encountered when using Internet search engines in quantitative linguistic research (such as non-transparent ranking algorithms). (ii) Creating a corpus from web data is virtually free. (iii) The size of corpora compiled from the WWW may exceed by several orders of magnitudes the size of language resources offered elsewhere. (iv) The data is locally available to the user, and it can be linguistically post-processed and queried with the tools preferred by her/him. This book addresses the main practical tasks in the creation of web corpora up to giga-token size. Among these tasks are the sampling process (i.e., web crawling) and the usual cleanups including boilerplate removal and removal of duplicated content. Linguistic processing and problems with linguistic processing coming from the different kinds of noise in web corpora are also covered. Finally, the authors show how web corpora can be evaluated and compared to other corpora (such as traditionally compiled corpora).

Автор: Scott
Название: Translation, Brains and the Computer
ISBN: 3319766287 ISBN-13(EAN): 9783319766287
Издательство: Springer
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Цена: 130430.00 T
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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: Moorkens
Название: Translation Quality Assessment
ISBN: 3319912402 ISBN-13(EAN): 9783319912400
Издательство: Springer
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Цена: 149060.00 T
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Описание: This is the first volume that brings together research and practice from academic and industry settings and a combination of human and machine translation evaluation. Its comprehensive collection of papers by leading experts in human and machine translation quality and evaluation who situate current developments and chart future trends fills a clear gap in the literature. This is critical to the successful integration of translation technologies in the industry today, where the lines between human and machine are becoming increasingly blurred by technology: this affects the whole translation landscape, from students and trainers to project managers and professionals, including in-house and freelance translators, as well as, of course, translation scholars and researchers. The editors have broad experience in translation quality evaluation research, including investigations into professional practice with qualitative and quantitative studies, and the contributors are leading experts in their respective fields, providing a unique set of complementary perspectives on human and machine translation quality and evaluation, combining theoretical and applied approaches.

Автор: Meng Ji, Michael Oakes
Название: Advances in Empirical Translation Studies : Developing Translation Resources and Technologies
ISBN: 1108423272 ISBN-13(EAN): 9781108423274
Издательство: Cambridge Academ
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Цена: 105600.00 T
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Описание: An advanced resource for a rapidly evolving research field, aimed at students and academics of translation studies and related fields such as applied linguistics, corpus linguistics, translation technology and digital humanities.

Автор: Manfred Stede, Jodi Schneider
Название: Argumentation Mining
ISBN: 1681734613 ISBN-13(EAN): 9781681734613
Издательство: Mare Nostrum (Eurospan)
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Цена: 97950.00 T
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Описание: Argumentation mining is an application of natural language processing (NLP) that emerged a few years ago and has recently enjoyed considerable popularity, as demonstrated by a series of international workshops and by a rising number of publications at the major conferences and journals of the field. Its goals are to identify argumentation in text or dialogue; to construct representations of the constellation of claims, supporting and attacking moves (in different levels of detail); and to characterize the patterns of reasoning that appear to license the argumentation. Furthermore, recent work also addresses the difficult tasks of evaluating the persuasiveness and quality of arguments. Some of the linguistic genres that are being studied include legal text, student essays, political discourse and debate, newspaper editorials, scientific writing, and others.The book starts with a discussion of the linguistic perspective, characteristics of argumentative language, and their relationship to certain other notions such as subjectivity.Besides the connection to linguistics, argumentation has for a long time been a topic in Artificial Intelligence, where the focus is on devising adequate representations and reasoning formalisms that capture the properties of argumentative exchange. It is generally very difficult to connect the two realms of reasoning and text analysis, but we are convinced that it should be attempted in the long term, and therefore we also touch upon some fundamentals of reasoning approaches.Then the book turns to its focus, the computational side of mining argumentation in text. We first introduce a number of annotated corpora that have been used in the research. From the NLP perspective, argumentation mining shares subtasks with research fields such as subjectivity and sentiment analysis, semantic relation extraction, and discourse parsing. Therefore, many technical approaches are being borrowed from those (and other) fields. We break argumentation mining into a series of subtasks, starting with the preparatory steps of classifying text as argumentative (or not) and segmenting it into elementary units. Then, central steps are the automatic identification of claims, and finding statements that support or oppose the claim. For certain applications, it is also of interest to compute a full structure of an argumentative constellation of statements. Next, we discuss a few steps that try to 'dig deeper': to infer the underlying reasoning pattern for a textual argument, to reconstruct unstated premises (so-called 'enthymemes'), and to evaluate the quality of the argumentation. We also take a brief look at 'the other side' of mining, i.e., the generation or synthesis of argumentative text.The book finishes with a summary of the argumentation mining tasks, a sketch of potential applications, and a-necessarily subjective-outlook for the field.

Автор: Horacio Saggion
Название: Automatic Text Simplification
ISBN: 1627058680 ISBN-13(EAN): 9781627058681
Издательство: Mare Nostrum (Eurospan)
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Цена: 51750.00 T
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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: Philip Williams, Michael Gertz, Matt Post, Philipp Koehn
Название: Syntax-based Statistical Machine Translation
ISBN: 1627059008 ISBN-13(EAN): 9781627059008
Издательство: Mare Nostrum (Eurospan)
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Цена: 72070.00 T
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Описание: Provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. The heart of this book is a detailed introduction to decoding for syntax-based models.

Автор: Jeffrey Heinz, Colin de la Higuera, Menno van Zaanen
Название: Grammatical Inference for Computational Linguistics
ISBN: 1608459772 ISBN-13(EAN): 9781608459773
Издательство: Mare Nostrum (Eurospan)
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Цена: 46200.00 T
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Описание: Provides a thorough introduction to the subfield of theoretical computer science known as grammatical inference from a computational linguistic perspective. Grammatical inference provides principled methods for developing computationally sound algorithms that learn structure from strings of symbols.

Автор: Michael Piotrowski
Название: Natural Language Processing for Historical Texts
ISBN: 1608459462 ISBN-13(EAN): 9781608459469
Издательство: Mare Nostrum (Eurospan)
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Цена: 46200.00 T
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Описание: Provides an introduction to natural language processing (NLP) for historical texts and an overview of the state of the art in this field. The book offers overview of methods for the acquisition of historical texts, discusses specific methods, and analyses the relationship between NLP and the digital humanities.

Автор: Inderjeet Mani
Название: Computational Modeling of Narrative
ISBN: 1608459810 ISBN-13(EAN): 9781608459810
Издательство: Mare Nostrum (Eurospan)
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Цена: 41580.00 T
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Описание: Provides an overview of the principal problems, approaches, and challenges faced today in modelling the narrative structure of stories. The book introduces classical narratological concepts from literary theory and their mapping to computational approaches. It also demonstrates how research in AI and NLP has modeled character goals, causality, and time.