Hybrid Approaches To Machine Translation

Author: Marta R. Costa-jussà
Publisher: Springer
ISBN: 3319213113
Size: 30.50 MB
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This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-processing for both types of MT architectures. The book is of interest primarily to MT specialists, but also – in the wider fields of Computational Linguistics, Machine Learning and Data Mining – to translators and managers of translation companies and departments who are interested in recent developments concerning automated translation tools.

Handbook Of Natural Language Processing

Author: Robert Dale
Publisher: CRC Press
ISBN: 0824746341
Size: 59.85 MB
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This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and artificial neural networks. It emphasizes the practical tools to accommodate the selected system.

Intelligent Natural Language Processing Trends And Applications

Author: Khaled Shaalan
Publisher: Springer
ISBN: 3319670565
Size: 78.26 MB
Format: PDF
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This book brings together scientists, researchers, practitioners, and students from academia and industry to present recent and ongoing research activities concerning the latest advances, techniques, and applications of natural language processing systems, and to promote the exchange of new ideas and lessons learned. Taken together, the chapters of this book provide a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of intelligent natural language processing. The book presents the state-of-the-art in research on natural language processing, computational linguistics, applied Arabic linguistics and related areas. New trends in natural language processing systems are rapidly emerging – and finding application in various domains including education, travel and tourism, and healthcare, among others. Many issues encountered during the development of these applications can be resolved by incorporating language technology solutions. The topics covered by the book include: Character and Speech Recognition; Morphological, Syntactic, and Semantic Processing; Information Extraction; Information Retrieval and Question Answering; Text Classification and Text Mining; Text Summarization; Sentiment Analysis; Machine Translation Building and Evaluating Linguistic Resources; and Intelligent Language Tutoring Systems.

Handbook Of Natural Language Processing And Machine Translation

Author: Joseph Olive
Publisher: Springer Science & Business Media
ISBN: 9781441977137
Size: 51.67 MB
Format: PDF
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This comprehensive handbook, written by leading experts in the field, details the groundbreaking research conducted under the breakthrough GALE program--The Global Autonomous Language Exploitation within the Defense Advanced Research Projects Agency (DARPA), while placing it in the context of previous research in the fields of natural language and signal processing, artificial intelligence and machine translation. The most fundamental contrast between GALE and its predecessor programs was its holistic integration of previously separate or sequential processes. In earlier language research programs, each of the individual processes was performed separately and sequentially: speech recognition, language recognition, transcription, translation, and content summarization. The GALE program employed a distinctly new approach by executing these processes simultaneously. Speech and language recognition algorithms now aid translation and transcription processes and vice versa. This combination of previously distinct processes has produced significant research and performance breakthroughs and has fundamentally changed the natural language processing and machine translation fields. This comprehensive handbook provides an exhaustive exploration into these latest technologies in natural language, speech and signal processing, and machine translation, providing researchers, practitioners and students with an authoritative reference on the topic.

The Handbook Of Computational Linguistics And Natural Language Processing

Author: Alexander Clark
Publisher: John Wiley & Sons
ISBN: 1118448677
Size: 24.73 MB
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This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forward Includes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has produced Presents the major developments in an accessible way, explaining the close connection between scientific understanding of the computational properties of natural language and the creation of effective language technologies Serves as an invaluable state-of-the-art reference source for computational linguists and software engineers developing NLP applications in industrial research and development labs of software companies

Foundations Of Statistical Natural Language Processing

Author: Christopher D. Manning
Publisher: MIT Press
ISBN: 9780262133609
Size: 53.16 MB
Format: PDF
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An introduction to statistical natural language processing (NLP). The text contains the theory and algorithms needed for building NLP tools. Topics covered include: mathematical and linguistic foundations; statistical methods; collocation finding; word sense disambiguation; and probalistic parsing.

Coarse To Fine Natural Language Processing

Author: Slav Petrov
Publisher: Springer Science & Business Media
ISBN: 9783642227431
Size: 64.72 MB
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The impact of computer systems that can understand natural language will be tremendous. To develop this capability we need to be able to automatically and efficiently analyze large amounts of text. Manually devised rules are not sufficient to provide coverage to handle the complex structure of natural language, necessitating systems that can automatically learn from examples. To handle the flexibility of natural language, it has become standard practice to use statistical models, which assign probabilities for example to the different meanings of a word or the plausibility of grammatical constructions. This book develops a general coarse-to-fine framework for learning and inference in large statistical models for natural language processing. Coarse-to-fine approaches exploit a sequence of models which introduce complexity gradually. At the top of the sequence is a trivial model in which learning and inference are both cheap. Each subsequent model refines the previous one, until a final, full-complexity model is reached. Applications of this framework to syntactic parsing, speech recognition and machine translation are presented, demonstrating the effectiveness of the approach in terms of accuracy and speed. The book is intended for students and researchers interested in statistical approaches to Natural Language Processing. Slav’s work Coarse-to-Fine Natural Language Processing represents a major advance in the area of syntactic parsing, and a great advertisement for the superiority of the machine-learning approach. Eugene Charniak (Brown University)

Natural Language Processing And Information Systems

Author: Flavius Frasincar
Publisher: Springer
ISBN: 3319595695
Size: 29.73 MB
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This book constitutes the refereed proceedings of the 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, held in Liège, Belgium, in June 2017. The 22 full papers, 19 short papers, and 16 poster papers presented were carefully reviewed and selected from 125 submissions. The papers are organized in the following topical sections: feature engineering; information extraction; information extraction from resource-scarce languages; natural language processing applications; neural language models and applications; opinion mining and sentiment analysis; question answering systems and applications; semantics-based models and applications; and text summarization.

Arabic Natural Language Processing

Author: Nizar Y. Habash
Publisher: Morgan & Claypool Publishers
ISBN: 1598297953
Size: 60.45 MB
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This book provides system developers and researchers in natural language processing and computational linguistics with the necessary background information for working with the Arabic language. The goal is to introduce Arabic linguistic phenomena and review the state-of-the-art in Arabic processing. The book discusses Arabic script, phonology, orthography, morphology, syntax and semantics, with a final chapter on machine translation issues. The chapter sizes correspond more or less to what is linguistically distinctive about Arabic, with morphology getting the lion's share, followed by Arabic script. No previous knowledge of Arabic is needed. This book is designed for computer scientists and linguists alike. The focus of the book is on Modern Standard Arabic; however, notes on practical issues related to Arabic dialects and languages written in the Arabic script are presented in different chapters. Table of Contents: What is "Arabic"? / Arabic Script / Arabic Phonology and Orthography / Arabic Morphology / Computational Morphology Tasks / Arabic Syntax / A Note on Arabic Semantics / A Note on Arabic and Machine Translation