Download or read book Data driven Machine Translation Using Semantic Tree Alignment written by Tom Vanallemeersch and published by . This book was released on 2018 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation deals with the improvement of systems for machine translation (MT) using semantic information. Such information tends to remain constant during translation, while the syntactic structure of sentences often changes, as a result of linguistic necessities or translators' choices. These changes make it difficult to derive syntactic rules automatically when building a statistical MT system (a type of data-driven system) using a substantial amount of sentences and their translation. For instance, the verb in a subordinaute clause must be moved after the direct object when translating from English to Dutch. Another example relates to the verb like: when translating it to bevallen ('please') in Dutch, the direct object becomes the subject. Constructing a syntax-based statistical MT system involves the automated alignment of words, the creation of a phrase table with the translation of words and word groups, and the derivation of translation rules based on syntactic trees produced by a parser.0In this dissertation, we investigate whether a semantic analysis of sentences and their translation facilitates the creation of translation rules and improves the quality of rules.

Download or read book Hybrid Approaches to Machine Translation written by Marta R. Costa-jussà and published by Springer. This book was released on 2016-07-21 with total page 0 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.

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.

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.

Download or read book Machine Translation From Research to Real Users written by Association for Machine Translation in the Americas. Conference and published by Springer Science & Business Media. This book was released on 2002-09-24 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th Conference of the Association for Machine Translation in the Americas, AMTA 2002, held in Tiburon, CA, USA, in October 2002. The 18 revised full technical papers, 3 user studies, and 9 system descriptions presented were carefully reviewed and selected for inclusion in the book. Among the issues addressed are hybrid translation environments, resource-limited MT, statistical word-level alignment, word formation rules, rule learning, web-based MT, translation divergences, example-based MT, data-driven MT, classification, contextual translation, the lexicon building process, commercial MT systems, speeck-to-speech translation, and language checking systems.

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.

Download or read book Bitext Alignment written by Jörg Tiedemann and published by Morgan & Claypool Publishers. This book was released on 2011-05-05 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of various techniques for the alignment of bitexts. It describes general concepts and strategies that can be applied to map corresponding parts in parallel documents on various levels of granularity. Bitexts are valuable linguistic resources for many different research fields and practical applications. The most predominant application is machine translation, in particular, statistical machine translation. However, there are various other threads that can be followed which may be supported by the rich linguistic knowledge implicitly stored in parallel resources. Bitexts have been explored in lexicography, word sense disambiguation, terminology extraction, computer-aided language learning and translation studies to name just a few. The book covers the essential tasks that have to be carried out when building parallel corpora starting from the collection of translated documents up to sub-sentential alignments. In particular, it describes various approaches to document alignment, sentence alignment, word alignment and tree structure alignment. It also includes a list of resources and a comprehensive review of the literature on alignment techniques. Table of Contents: Introduction / Basic Concepts and Terminology / Building Parallel Corpora / Sentence Alignment / Word Alignment / Phrase and Tree Alignment / Concluding Remarks

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 241 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.

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.

Download or read book Parallel Text Processing written by Jean Véronis and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: l This book evolved from the ARCADE evaluation exercise that started in 1995. The project's goal is to evaluate alignment systems for parallel texts, i. e. , texts accompanied by their translation. Thirteen teams from various places around the world have participated so far and for the first time, some ten to fifteen years after the first alignment techniques were designed, the community has been able to get a clear picture of the behaviour of alignment systems. Several chapters in this book describe the details of competing systems, and the last chapter is devoted to the description of the evaluation protocol and results. The remaining chapters were especially commissioned from researchers who have been major figures in the field in recent years, in an attempt to address a wide range of topics that describe the state of the art in parallel text processing and use. As I recalled in the introduction, the Rosetta stone won eternal fame as the prototype of parallel texts, but such texts are probably almost as old as the invention of writing. Nowadays, parallel texts are electronic, and they are be coming an increasingly important resource for building the natural language processing tools needed in the "multilingual information society" that is cur rently emerging at an incredible speed. Applications are numerous, and they are expanding every day: multilingual lexicography and terminology, machine and human translation, cross-language information retrieval, language learning, etc.

Download or read book From Syntax to Semantics written by Erich Steiner and published by Intellect Books. This book was released on 1988 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine translation is a central aspect of research in artifical intelligence. This book is written in the context of the Machine Translation (MT) project EUROTRA, a multi-lingual MT-project putting special emphasis on the definition of semantic representation.

Download or read book Machine Translation written by Sergei Nirenburg and published by Morgan Kaufmann. This book was released on 1992 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: All over the world, people are claiming their rights. Are these claims prompted by similar values and aspirations? And even if human rights are universal, what are the consequences of claiming them in different historical, cultural and material realities? The diversity of African countries considered in this book compels careful thought about these questions.

Download or read book Towards Semantic based Machine Translation written by Ding Liu and published by . This book was released on 2010 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Syntax-based statistical machine translation (MT) systems are superior to the old phrase-based MT systems in that they use tree-to-string templates to model long- distance re-ordering in between two languages and generate more fluent sentences. We show ways to improve a tree-to-string transducer by: 1. Adding a sub-tree bigram based tree decomposition model. 2. Computing better word alignments based on a syntax-based alignment model. 3. Directly learning tree-to-string (TTS) templates from the data based on a Bayesian model with Dirichlet process prior. To incorporate semantic role features into a syntax-based MT system, we propose a conditional log-linear framework where feature weights can be effectively tuned. We show better translation results based on manual evaluation. Automatic evaluation is crucial to the development of MT systems, especially when modern MT systems begin using the evaluation metrics in the system tuning. We propose metrics based on the syntactic structure of a MT output sentence to better evaluate its fluency, as well as the other novel metrics based on stochastic word matching, iterative word alignment, and source-language constraints to better correlate with the human judgments. To make the best use of the strength of each individual metric, we also propose a linear model to combine different metrics together, and compute their weights by optimizing the combined metric's correlation with human judgments."--Leaf v.

Download or read book The KBMT Project written by Kenneth Goodman and published by Elsevier. This book was released on 1991-09-25 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine translation of natural languages is one of the most complex and comprehensive applications of computational linguistics and artificial intelligence. This is especially true of knowledge-based machine translation (KBMT) systems, which require many knowledge resources and processing modules to carry out the necessary levels of analysis, representation and generation of meaning and form. The number of real-world problems, tasks, and solutions involved in developing any realistic-size knowledge-based machine translation system is enormous. It is thus difficult for researchers in the field to learn what a system "really does". This book fills that need with a detailed case study of a KBMT system implemented at the Center for Machine Translation at Carnegie Mellon University. The research consists in part of the creation of a system for translation between English and Japanese. The corpora used in the project were manuals for installing and maintaining IBM personal computers (sponsorship by IBM, through its Tokyo Research Laboratory) Individual chapters describe the interlingua texts used in knowledge-based machine translation, the grammar formalism embodied in the system, the grammars and lexicons and their roles in the translation process, the process of source language analysis, an augmentation module that interactively and automatically resolves ambiguities remaining after source language analysis, and the generator, which produces target language sentences. Detailed appendices illustrate the process from analysis through generation. This book is intended for developers, researchers and advanced students in natural language processing and computational linguistics, including all those who have an interest in machine translation and machine-aided translation.

Download or read book Handbook of Natural Language Processing and Machine Translation written by Joseph Olive and published by Springer Science & Business Media. This book was released on 2011-03-02 with total page 956 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Using Comparable Corpora for Under Resourced Areas of Machine Translation written by Inguna Skadiņa and published by Springer. This book was released on 2019-02-06 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of how comparable corpora can be used to overcome the lack of parallel resources when building machine translation systems for under-resourced languages and domains. It presents a wealth of methods and open tools for building comparable corpora from the Web, evaluating comparability and extracting parallel data that can be used for the machine translation task. It is divided into several sections, each covering a specific task such as building, processing, and using comparable corpora, focusing particularly on under-resourced language pairs and domains. The book is intended for anyone interested in data-driven machine translation for under-resourced languages and domains, especially for developers of machine translation systems, computational linguists and language workers. It offers a valuable resource for specialists and students in natural language processing, machine translation, corpus linguistics and computer-assisted translation, and promotes the broader use of comparable corpora in natural language processing and computational linguistics.

Download or read book Towards High precision Machine Translation written by John Laffling and published by . This book was released on 1991 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: