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 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 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 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 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 Morphological Analysis for Statistical Machine Translation written by and published by . This book was released on 2004 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present a novel morphological analysis technique which induces a morphological and syntactic symmetry between two languages with highly asymmetrical morphological structures to improve statistical machine translation qualities. The technique pre-supposes fine-grained segmentation of a word in the morphologically rich language into the sequence of prefix(es)-stem-suffix(es) and part-of-speech tagging of the parallel corpus. The algorithm identifies morphemes to be merged or deleted in the morphologically rich language to induce the desired morphological and syntactic symmetry. The technique improves Arabic-to-English translation qualities significantly when applied to IBM Model 1 and Phrase Translation Models trained on the training corpus size ranging from 3,500 to 3.3 million sentence pairs.

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 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 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 Introduction to Arabic Natural Language Processing written by Nizar Y. Habash and published by Springer Nature. This book was released on 2022-06-01 with total page 170 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 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 Morphology Modeling for Statistical Machine Translation written by Kadriye Elif Eyigoz and published by . This book was released on 2014 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Word-alignment is the initial step in most state-of-the art approaches to statistical machine translation. Morphologically rich languages pose problems for current statistical machine translation systems, including word-alignment, the most common problem being data sparsity. Current word-alignment models do not take into account morphology beyond merely treating morphemes as words. We present a new word alignment model that distinguishes between words and morphemes. Our model does not collapse words and morphemes into one single category, therefore we can legitimately talk about words and their morphemes in line with the linguistic conception of these terms. We adopt a two-level representation of alignment: the first level involves word alignment, the second level involves morpheme alignment in the scope of a given word alignment. Two-level alignment models (TAM) can align rarely occurring words through their frequently occurring morphemes. Our model induces word and morpheme alignments jointly using the expectation maximization algorithm. We present the HMM extension of TAM, which is an instance of a multi-scale HMM. The two-level HMM we present addresses reordering between morpheme positions and word positions simultaneously"--Page vi.

Download or read book Two level Morphology written by Kimmo Koskenniemi and published by . This book was released on 1983 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advances in Artificial Intelligence and Its Applications written by Félix Castro and published by Springer. This book was released on 2013-11-22 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 8265 and LNAI 8266 constitutes the proceedings of the 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, held in Mexico City, Mexico, in November 2013. The total of 85 papers presented in these proceedings were carefully reviewed and selected from 284 submissions. The first volume deals with advances in artificial intelligence and its applications and is structured in the following five sections: logic and reasoning; knowledge-based systems and multi-agent systems; natural language processing; machine translation; and bioinformatics and medical applications. The second volume deals with advances in soft computing and its applications and is structured in the following eight sections: evolutionary and nature-inspired metaheuristic algorithms; neural networks and hybrid intelligent systems; fuzzy systems; machine learning and pattern recognition; data mining; computer vision and image processing; robotics, planning and scheduling and emotion detection, sentiment analysis and opinion mining.

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 Natural Language Processing of Semitic Languages written by Imed Zitouni and published by Springer Science & Business. This book was released on 2014-04-22 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Natural Language Processing (NLP) has rapidly advanced in recent years, resulting in exciting algorithms for sophisticated processing of text and speech in various languages. Much of this work focuses on English; in this book we address another group of interesting and challenging languages for NLP research: the Semitic languages. The Semitic group of languages includes Arabic (206 million native speakers), Amharic (27 million), Hebrew (7 million), Tigrinya (6.7 million), Syriac (1 million) and Maltese (419 thousand). Semitic languages exhibit unique morphological processes, challenging syntactic constructions and various other phenomena that are less prevalent in other natural languages. These challenges call for unique solutions, many of which are described in this book. The 13 chapters presented in this book bring together leading scientists from several universities and research institutes worldwide. While this book devotes some attention to cutting-edge algorithms and techniques, its primary purpose is a thorough explication of best practices in the field. Furthermore, every chapter describes how the techniques discussed apply to Semitic languages. The book covers both statistical approaches to NLP, which are dominant across various applications nowadays and the more traditional, rule-based approaches, that were proven useful for several other application domains. We hope that this book will provide a "one-stop-shop'' for all the requisite background and practical advice when building NLP applications for Semitic languages.

Download or read book Computational Linguistics and Intelligent Text Processing written by Alexander Gelbukh and published by Springer. This book was released on 2013-03-12 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set, consisting of LNCS 7816 and LNCS 7817, constitutes the thoroughly refereed proceedings of the 13th International Conference on Computer Linguistics and Intelligent Processing, CICLING 2013, held on Samos, Greece, in March 2013. The total of 91 contributions presented was carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections named: general techniques; lexical resources; morphology and tokenization; syntax and named entity recognition; word sense disambiguation and coreference resolution; semantics and discourse; sentiment, polarity, subjectivity, and opinion; machine translation and multilingualism; text mining, information extraction, and information retrieval; text summarization; stylometry and text simplification; and applications.