Using Linguistic Knowledge In Statistical Machine Translation

Download Using Linguistic Knowledge In Statistical Machine Translation full books in PDF, epub, and Kindle. Read online Using Linguistic Knowledge In Statistical Machine Translation ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Using Linguistic Knowledge in Statistical Machine Translation

Author : Rabih Mohamed Zbib
Publisher :
ISBN 13 :
Total Pages : 162 pages
Book Rating : 4.:/5 (71 download)

DOWNLOAD NOW!

Book Synopsis Using Linguistic Knowledge in Statistical Machine Translation by : Rabih Mohamed Zbib

Download or read book Using Linguistic Knowledge in Statistical Machine Translation written by Rabih Mohamed Zbib and published by . This book was released on 2010 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we present methods for using linguistically motivated information to enhance the performance of statistical machine translation (SMT). One of the advantages of the statistical approach to machine translation is that it is largely language-agnostic. Machine learning models are used to automatically learn translation patterns from data. SMT can, however, be improved by using linguistic knowledge to address specific areas of the translation process, where translations would be hard to learn fully automatically. We present methods that use linguistic knowledge at various levels to improve statistical machine translation, focusing on Arabic-English translation as a case study. In the first part, morphological information is used to preprocess the Arabic text for Arabic-to-English and English-to-Arabic translation, which reduces the gap in the complexity of the morphology between Arabic and English. The second method addresses the issue of long-distance reordering in translation to account for the difference in the syntax of the two languages. In the third part, we show how additional local context information on the source side is incorporated, which helps reduce lexical ambiguity. Two methods are proposed for using binary decision trees to control the amount of context information introduced. These methods are successfully applied to the use of diacritized Arabic source in Arabic-to-English translation. The final method combines the outputs of an SMT system and a Rule-based MT (RBMT) system, taking advantage of the flexibility of the statistical approach and the rich linguistic knowledge embedded in the rule-based MT system.

Linguistically Motivated Statistical Machine Translation

Author : Deyi Xiong
Publisher : Springer
ISBN 13 : 9812873562
Total Pages : 159 pages
Book Rating : 4.8/5 (128 download)

DOWNLOAD NOW!

Book Synopsis Linguistically Motivated Statistical Machine Translation by : Deyi Xiong

Download or read book Linguistically Motivated Statistical Machine Translation written by Deyi Xiong and published by Springer. This book was released on 2015-02-11 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.

Introducing linguistic knowledge into statistical machine translation[

Author : Adrià Gispert Ramis
Publisher :
ISBN 13 : 9788469055632
Total Pages : pages
Book Rating : 4.0/5 (556 download)

DOWNLOAD NOW!

Book Synopsis Introducing linguistic knowledge into statistical machine translation[ by : Adrià Gispert Ramis

Download or read book Introducing linguistic knowledge into statistical machine translation[ written by Adrià Gispert Ramis and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Translation

Author : Maja Popović
Publisher :
ISBN 13 :
Total Pages : 114 pages
Book Rating : 4.:/5 (51 download)

DOWNLOAD NOW!

Book Synopsis Machine Translation by : Maja Popović

Download or read book Machine Translation written by Maja Popović and published by . This book was released on 2009 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Challenges for Arabic Machine Translation

Author : Abdelhadi Soudi
Publisher : John Benjamins Publishing
ISBN 13 : 9027273626
Total Pages : 167 pages
Book Rating : 4.0/5 (272 download)

DOWNLOAD NOW!

Book Synopsis Challenges for Arabic Machine Translation by : Abdelhadi Soudi

Download or read book Challenges for Arabic Machine Translation written by Abdelhadi Soudi and published by John Benjamins Publishing. This book was released on 2012-08-01 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first volume that focuses on the specific challenges of machine translation with Arabic either as source or target language. It nicely fills a gap in the literature by covering approaches that belong to the three major paradigms of machine translation: Example-based, statistical and knowledge-based. It provides broad but rigorous coverage of the methods for incorporating linguistic knowledge into empirical MT. The book brings together original and extended contributions from a group of distinguished researchers from both academia and industry. It is a welcome and much-needed repository of important aspects in Arabic Machine Translation such as morphological analysis and syntactic reordering, both central to reducing the distance between Arabic and other languages. Most of the proposed techniques are also applicable to machine translation of Semitic languages other than Arabic, as well as translation of other languages with a complex morphology.

Hybrid Approaches to Machine Translation

Author : Marta R. Costa-jussà
Publisher : Springer
ISBN 13 : 3319213113
Total Pages : 208 pages
Book Rating : 4.3/5 (192 download)

DOWNLOAD NOW!

Book Synopsis Hybrid Approaches to Machine Translation by : Marta R. Costa-jussà

Download or read book Hybrid Approaches to Machine Translation written by Marta R. Costa-jussà and published by Springer. This book was released on 2016-07-12 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Syntax-based Statistical Machine Translation

Author : Philip Williams
Publisher : Springer Nature
ISBN 13 : 3031021649
Total Pages : 190 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Syntax-based Statistical Machine Translation by : Philip Williams

Download or read book Syntax-based Statistical Machine Translation written by Philip Williams and published by Springer Nature. This book was released on 2022-05-31 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book 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. While phrase-based models have previously dominated the field, syntax-based approaches have proved a popular alternative, as they elegantly solve many of the shortcomings of phrase-based models. The heart of this book is a detailed introduction to decoding for syntax-based models. The book begins with an overview of synchronous-context free grammar (SCFG) and synchronous tree-substitution grammar (STSG) along with their associated statistical models. It also describes how three popular instantiations (Hiero, SAMT, and GHKM) are learned from parallel corpora. It introduces and details hypergraphs and associated general algorithms, as well as algorithms for decoding with both tree and string input. Special attention is given to efficiency, including search approximations such as beam search and cube pruning, data structures, and parsing algorithms. The book consistently highlights the strengths (and limitations) of syntax-based approaches, including their ability to generalize phrase-based translation units, their modeling of specific linguistic phenomena, and their function of structuring the search space.

Statistical Language Learning

Author : Eugene Charniak
Publisher : MIT Press
ISBN 13 : 9780262531412
Total Pages : 196 pages
Book Rating : 4.5/5 (314 download)

DOWNLOAD NOW!

Book Synopsis Statistical Language Learning by : Eugene Charniak

Download or read book Statistical Language Learning written by Eugene Charniak and published by MIT Press. This book was released on 1996 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text introduces statistical language processing techniques--word tagging, parsing with probabilistic context free grammars, grammar induction, syntactic disambiguation, semantic word classes, word-sense disambiguation--along with the underlying mathematics and chapter exercises.

Recent Advances in Example-Based Machine Translation

Author : M. Carl
Publisher : Springer Science & Business Media
ISBN 13 : 9401001812
Total Pages : 524 pages
Book Rating : 4.4/5 (1 download)

DOWNLOAD NOW!

Book Synopsis Recent Advances in Example-Based Machine Translation by : M. Carl

Download or read book Recent Advances in Example-Based Machine Translation written by M. Carl and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent Advances in Example-Based Machine Translation is of relevance to researchers and program developers in the field of Machine Translation and especially Example-Based Machine Translation, bilingual text processing and cross-linguistic information retrieval. It is also of interest to translation technologists and localisation professionals. Recent Advances in Example-Based Machine Translation fills a void, because it is the first book to tackle the issue of EBMT in depth. It gives a state-of-the-art overview of EBMT techniques and provides a coherent structure in which all aspects of EBMT are embedded. Its contributions are written by long-standing researchers in the field of MT in general, and EBMT in particular. This book can be used in graduate-level courses in machine translation and statistical NLP.

Translation, Brains and the Computer

Author : Bernard Scott
Publisher : Springer
ISBN 13 : 3319766295
Total Pages : 249 pages
Book Rating : 4.3/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Translation, Brains and the Computer by : Bernard Scott

Download or read book Translation, Brains and the Computer written by Bernard Scott and published by Springer. This book was released on 2018-06-06 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introducing Linguistic Knowledge Into Statistical Machine Translation

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (65 download)

DOWNLOAD NOW!

Book Synopsis Introducing Linguistic Knowledge Into Statistical Machine Translation by :

Download or read book Introducing Linguistic Knowledge Into Statistical Machine Translation written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: RESUM Aquesta tesi està dedicada a l'estudi de la utilització de informació morfosintàctica en el marc dels sistemes de traducció estocàstica, amb l'objectiu de millorar-ne la qualitat a través de la incorporació de informació lingüística més enllà del nivell simbòlic superficial de les paraules. El sistema de traducció estocàstica utilitzat en aquest treball segueix un enfocament basat en tuples, unitats bilingües que permeten estimar un model de traducció de probabilitat conjunta per mitjà de la combinació, dins un entorn log-linial, de cadenes d'n-grames i funcions característiques addicionals. Es presenta un estudi detallat d'aquesta aproximació, que inclou la seva transformació des d'una implementació d'X-grames en autòmats d'estats finits, més orientada a la traducció de veu, cap a l'actual solució d'n-grames orientada a la traducció de text de gran vocabulari. La tesi estudia també les fases d'entrenament i decodificació, així com el rendiment per a diferents tasques (variant el tamany dels corpora o el parell d'idiomes) i els principals problemes reflectits en les anàlisis d'error. La tesis també investiga la incorporació de informació lingüística específicament en aliniament per paraules. Es proposa l'extensió mitjançant classificació de formes verbals d'un algorisme d'aliniament paraula a paraula basat en co-ocurrències, amb resultats positius. Així mateix, s'avalua de forma empírica l'impacte en qualitat d'aliniament i de traducció que s'obté mitjançant l'etiquetatge morfològic, la lematització, la classificació de formes verbals i el truncament o stemming del text parallel. Pel que fa al model de traducció, es proposa un model de tractament de les formes verbals per mitjà d'un model de instanciació addicional, i es realitzen experiments en la direcció d'anglès a castellà. La tesi també introdueix un model de llenguatge d'etiquetes morfològiques del destí per tal d'abordar problemes de concordança. Finalment, s'estudia l'impacte de la derivació morfològic.

Building and Using Comparable Corpora for Multilingual Natural Language Processing

Author : Serge Sharoff
Publisher : Springer Nature
ISBN 13 : 3031313844
Total Pages : 138 pages
Book Rating : 4.0/5 (313 download)

DOWNLOAD NOW!

Book Synopsis Building and Using Comparable Corpora for Multilingual Natural Language Processing by : Serge Sharoff

Download or read book Building and Using Comparable Corpora for Multilingual Natural Language Processing written by Serge Sharoff and published by Springer Nature. This book was released on 2023-08-23 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of methods to build comparable corpora and of their applications, including machine translation, cross-lingual transfer, and various kinds of multilingual natural language processing. The authors begin with a brief history on the topic followed by a comparison to parallel resources and an explanation of why comparable corpora have become more widely used. In particular, they provide the basis for the multilingual capabilities of pre-trained models, such as BERT or GPT. The book then focuses on building comparable corpora, aligning their sentences to create a database of suitable translations, and using these sentence translations to produce dictionaries and term banks. Then, it is explained how comparable corpora can be used to build machine translation engines and to develop a wide variety of multilingual applications.

Statistical Machine Translation

Author : Philipp Koehn
Publisher : Cambridge University Press
ISBN 13 : 0521874157
Total Pages : 447 pages
Book Rating : 4.5/5 (218 download)

DOWNLOAD NOW!

Book Synopsis Statistical Machine Translation by : Philipp Koehn

Download or read book Statistical Machine Translation written by Philipp Koehn and published by Cambridge University Press. This book was released on 2010 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: The dream of automatic language translation is now closer thanks to recent advances in the techniques that underpin statistical machine translation. This class-tested textbook from an active researcher in the field, provides a clear and careful introduction to the latest methods and explains how to build machine translation systems for any two languages. It introduces the subject's building blocks from linguistics and probability, then covers the major models for machine translation: word-based, phrase-based, and tree-based, as well as machine translation evaluation, language modeling, discriminative training and advanced methods to integrate linguistic annotation. The book also reports the latest research, presents the major outstanding challenges, and enables novices as well as experienced researchers to make novel contributions to this exciting area. Ideal for students at undergraduate and graduate level, or for anyone interested in the latest developments in machine translation.

Machine Translation

Author : Thierry Poibeau
Publisher : MIT Press
ISBN 13 : 0262534215
Total Pages : 298 pages
Book Rating : 4.2/5 (625 download)

DOWNLOAD NOW!

Book Synopsis Machine Translation by : Thierry Poibeau

Download or read book Machine Translation written by Thierry Poibeau and published by MIT Press. This book was released on 2017-09-15 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and major players in the industry. The dream of a universal translation device goes back many decades, long before Douglas Adams's fictional Babel fish provided this service in The Hitchhiker's Guide to the Galaxy. Since the advent of computers, research has focused on the design of digital machine translation tools—computer programs capable of automatically translating a text from a source language to a target language. This has become one of the most fundamental tasks of artificial intelligence. This volume in the MIT Press Essential Knowledge series offers a concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and market potential. The main approaches are presented from a largely historical perspective and in an intuitive manner, allowing the reader to understand the main principles without knowing the mathematical details. The book begins by discussing problems that must be solved during the development of a machine translation system and offering a brief overview of the evolution of the field. It then takes up the history of machine translation in more detail, describing its pre-digital beginnings, rule-based approaches, the 1966 ALPAC (Automatic Language Processing Advisory Committee) report and its consequences, the advent of parallel corpora, the example-based paradigm, the statistical paradigm, the segment-based approach, the introduction of more linguistic knowledge into the systems, and the latest approaches based on deep learning. Finally, it considers evaluation challenges and the commercial status of the field, including activities by such major players as Google and Systran.

Readings in Machine Translation

Author : Sergei Nirenburg
Publisher : MIT Press
ISBN 13 : 9780262140744
Total Pages : 444 pages
Book Rating : 4.1/5 (47 download)

DOWNLOAD NOW!

Book Synopsis Readings in Machine Translation by : Sergei Nirenburg

Download or read book Readings in Machine Translation written by Sergei Nirenburg and published by MIT Press. This book was released on 2003 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of machine translation (MT) - the automation of translation between human languages - has existed for more than 50 years. MT helped to usher in the field of computational linguistics and has influenced methods and applications in knowledge representation, information theory, and mathematical statistics.

Quality Estimation for Machine Translation

Author : Lucia Specia
Publisher : Springer Nature
ISBN 13 : 3031021681
Total Pages : 148 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Quality Estimation for Machine Translation by : Lucia Specia

Download or read book Quality Estimation for Machine Translation written by Lucia Specia and published by Springer Nature. This book was released on 2022-05-31 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Translation with Minimal Reliance on Parallel Resources

Author : George Tambouratzis
Publisher : Springer
ISBN 13 : 3319631071
Total Pages : 92 pages
Book Rating : 4.3/5 (196 download)

DOWNLOAD NOW!

Book Synopsis Machine Translation with Minimal Reliance on Parallel Resources by : George Tambouratzis

Download or read book Machine Translation with Minimal Reliance on Parallel Resources written by George Tambouratzis and published by Springer. This book was released on 2017-08-09 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified view on a new methodology for Machine Translation (MT). This methodology extracts information from widely available resources (extensive monolingual corpora) while only assuming the existence of a very limited parallel corpus, thus having a unique starting point to Statistical Machine Translation (SMT). In this book, a detailed presentation of the methodology principles and system architecture is followed by a series of experiments, where the proposed system is compared to other MT systems using a set of established metrics including BLEU, NIST, Meteor and TER. Additionally, a free-to-use code is available, that allows the creation of new MT systems. The volume is addressed to both language professionals and researchers. Prerequisites for the readers are very limited and include a basic understanding of the machine translation as well as of the basic tools of natural language processing.