Download or read book Statistical Machine Translation of the Arabic Language written by Walid Aransa and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Arabic language received a lot of attention in the machine translation community during the last decade. It is the official language of 25 countries and it is spoken by more than 380 million people. The interest in Arabic language and its dialects increased more after the Arab spring and the political change in the Arab countries. In this thesis, I worked on improving LIUM's machine translation system for Arabic-English in the frame-work of the BOLT project.In this thesis, I have extend LIUM's phrase-based statistical machine translation system in many ways. Phrase-based systems are considered to be one of the best performing approaches. Basically, two probabilistic models are used, a translation model and a language model.I have been working on improving the translation quality. This is done by focusing on three different aspects. The first aspect is reducing the number of unknown words in the translated output. Second, the entities like numbers or dates that can be translated efficiently by some transfer rules. Finally, I have been working on the transliteration of named entities. The second aspect of my work is the adaptation of the translation model to the domain or genre of the translation task.Finally, I have been working on improved language modeling, based on neural network language models, also called continuous space language models. They are used to rescore the n-best translation hypotheses.All the developed techniques have been thoroughly evaluated and I took part in three international evaluations of the BOLT project.

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.

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 with total page 166 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.

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.

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.

Download or read book Morphological Solutions for Arabic Statistical Machine Translation and Sentiment Analysis written by Mohammad K. Salameh and published by . This book was released on 2016 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Morphologically complex languages such as Arabic pose several challenges in Natural Language Processing (NLP) due to their complexity and token sparsity. Most techniques approach the problem by transforming the words of the language from their sparse surface form representation to a less sparse form before processing. The transformation usually takes the form of a morphological analysis or a morphological segmentation. This dissertation addresses two tasks in Arabic NLP: Statistical Machine Translation (SMT) and Sentiment Analysis. To improve English-Arabic SMT, we apply segmentation on Arabic to decrease token sparsity and enhance the correspondence between tokens of the English and Arabic language. However, due to this segmentation, the translation system is limited to extracting features based on morphemes (partial words) and only outputting morphemes during decoding. Such a system lacks knowledge of the original form of the words. We further improve translation from English to Arabic by combining both segmented and desegmented views of the target language. The system can benefit from segmentation's sparsity reduction and verifies its generation of correct words. We present a language-independent technique to desegmentation that approaches the problem as a string transduction task. We propose a new algorithm that desegments the decoder's search space encoded as a lattice, thus allowing the system to use features from the desegmented view of the search space. We extend the phrase-based statistical machine translation system to allow desegmentation during the decoding process on the fly. In addition, we conduct an experimental study to verify what matters most in morphologically segmented SMT models. Our second task is sentiment analysis, where we resort to Arabic lemmatization to improve sentiment analysis of Arabic tweets and blog posts. We explore translation in the opposite direction, from Arabic into English in order to evaluate the loss of sentiment predictability when Arabic social media posts are translated to English, manually or using an SMT system. We use state-of-the-art Arabic and English sentiment Analysis systems and develop automatically generated Arabic lexicons from lemmatized tweets to improve this task.

Download or read book Introduction to Arabic Natural Language Processing written by Nizar Y. Habash and published by Morgan & Claypool Publishers. This book was released on 2010 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Performance Evaluation of the Factored Model for Arabic to English Phrase Based Statistical Machine Translation written by Mireille Anwar and published by . This book was released on 2008 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Creating a Strong Statistical Machine Translation System by Combining Different Decoders written by Ayah ElMaghraby and published by . This book was released on 2018 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Machine translation is a very important field in Natural Language Processing. The need for machine translation arises due to the increasing amount of data available online. Most of our data now is digital and this is expected to increase over time. Since human manual translation takes a lot of time and effort, machine translation is needed to cover all of the languages available. A lot of research has been done to make machine translation faster and more reliable between different language pairs. Machine translation is now being coupled with deep learning and neural networks. New topics in machine translation are being studied and tested like applying neural machine translation as a replacement to the classical statistical machine translation. In this thesis, we also study the effect of data-preprocessing and decoder type on translation output. We then demonstrate two ways to enhance translation from English to Arabic. The first approach uses a two-decoder system; the first decoder translates from English to Arabic and the second is a post-processing decoder that retranslates the first Arabic output to Arabic again to fix some of the translation errors. We then study the results of different kinds of decoders and their contributions to the test set. The results of this study lead to the second approach which combines different decoders to create a stronger one. The second approach uses a classifier to categorize the English sentences based on their structure. The output of the classifier is the decoder that is suited best to translate the English sentence. Both approaches increased the BLEU score albeit with different ranges. The classifier showed an increase of ~0.1 BLEU points while the post-processing decoder showed an increase of between ~0.3~11 BLEU points on two different test sets. Eventually we compare our results to Google translate to know how well we are doing in comparison to a well-known translator. Our best translation machine system scored 5 absolute points compared to Google translate in ISI corpus test set and we were 9 absolute points lower in the case of the UN corpus test set..

Download or read book A Practical Guide for Translators written by Geoffrey Samuelsson-Brown and published by Multilingual Matters. This book was released on 2010-03-24 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the fifth revised edition of the best-selling A Practical Guide for Translators. It looks at the profession of translator on the basis of developments over the last few years and encourages both practitioners and buyers of translation services to view translation as a highly-qualified, skilled profession and not just a cost-led word mill. The book is intended principally for those who have little or no practical experience of translation in a commercial environment. It offers comprehensive advice on all aspects relevant to the would-be translator and, whilst intended mainly for those who wish to go freelance, it is also relevant to the staff translator as a guide to organisation of work and time. Advice is given on how to set up as a translator, from the purchase of equipment to the acquisition of clients. The process of translation is discussed from initial enquiry to delivery of the finished product. Hints are given on how to assess requirements, how to charge for work, how to research and use source material, and how to present the finished product. Guidance is given on where to obtain further advice and professional contacts. This revised edition updates practices in the translation profession and considers the impact of web-based translation offerings. Industry and commerce rely heavily on the skills of the human translator and his ability to make intellectual decisions that is, as yet, beyond the capacity of computer-aided translation.

Download or read book Applying Morphology to English Arabic Statistical Machine Translation written by Soha Sultan and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analysing English Arabic Machine Translation written by Zakaryia Almahasees and published by Routledge. This book was released on 2021-11-30 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Translation (MT) has become widely used throughout the world as a medium of communication between those who live in different countries and speak different languages. However, translation between distant languages constitutes a challenge for machines. Therefore, translation evaluation is poised to play a significant role in the process of designing and developing effective MT systems. This book evaluates three prominent MT systems, including Google Translate, Microsoft Translator, and Sakhr, each of which provides translation between English and Arabic. In the book Almahasees scrutinizes the capacity of the three systems in dealing with translation between English and Arabic in a large corpus taken from various domains, including the United Nation (UN), the World Health Organization (WHO), the Arab League, Petra News Agency reports, and two literary texts: The Old Man and the Sea and The Prophet. The evaluation covers holistic analysis to assess the output of the three systems in terms of Translation Automation User Society (TAUS) adequacy and fluency scales. The text also looks at error analysis to evaluate the systems’ output in terms of orthography, lexis, grammar, and semantics at the entire-text level and in terms of lexis, grammar, and semantics at the collocation level. The research findings contained within this volume provide important feedback about the capabilities of the three MT systems with respect to EnglishArabic translation and paves the way for further research on such an important topic. This book will be of interest to scholars and students of translation studies and translation technology.

Download or read book Arabic Computational Morphology written by Abdelhadi Soudi and published by Springer Science & Business Media. This book was released on 2007-10-01 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive overview of computational approaches to Arabic morphology. The subtitle aims to reflect that widely different computational approaches to the Arabic morphological system have been proposed. The book provides a showcase of the most advanced language technologies applied to one of the most vexing problems in linguistics. It covers knowledge-based and empirical-based approaches.

Download or read book Neural Machine Translation written by Philipp Koehn and published by Cambridge University Press. This book was released on 2020-06-18 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.

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.

Download or read book Automatic Transliteration from Arabic to English and Its Impact on Machine Translation written by Mehdi Mostafavi Kashani and published by . This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Among various linguistic structures that can be used in a sentence, named entities are one of the most important and most informative.Transcribing them from one language into another is called transliteration. This thesis proposes a novel spelling-based method for the automatic transliteration of named entities from Arabic to English which exploits various types of letter-based alignments. The approach consists of three phases: the first phase uses single letter alignments, the second phase uses alignments over groups of letters to deal with diacritics and missing vowels in the English output, and the third phase exploits various knowledge sources to repair any remaining errors. The results show a top-20 accuracy rate of up to 88%. Our algorithm is examined in the context of a machine translation task. We provide an in-depth analysis of the integration of our Arabic-to-English transliteration system into a general-purpose phrase-based statistical machine translation system. We study the integration from different aspects and evaluate the improvement that can be attributed to the integration using the BLEU metric. Our experiments show that a transliteration module can help significantly in the situation where the test data is rich with previously unseen named entities.

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.