Analysing English Arabic Machine Translation

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.

"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 English-Arabic 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"--

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.

The key purpose of this work is to examine the interrelationship between the field of text linguistics and translation with specific reference to computer translation. The question arises whether machine translation can ever be a practicable and reliable substitute for human translators. Based on this premise, this study assesses the effectiveness of machine translation software in its ability to translate the nuances of text linguistics from a source language to a target language. Following a literature review of text linguistics covering a number of textual analysis models and translation studies including machine translation, the primary research utilises a qualitative research methodology by means of text-based assessment. Three text samples are drawn from each of the following six text linguistic categories: register, pragmatics, semiotics, text type, genre and discourse. Using three leading Arabic translation software programmes the text samples are subjected to a comparative evaluation.

This title is a comprehensive and practical 20-week course in translation method offering a challenging approach to the acquisition of translation skills.

A Reference Grammar of Modern Standard Arabic is a comprehensive handbook on the structure of Arabic. Keeping technical terminology to a minimum, it provides a detailed yet accessible overview of Modern Standard Arabic in which the essential aspects of its phonology, morphology and syntax can be readily looked up and understood. Accompanied by extensive carefully-chosen examples, it will prove invaluable as a practical guide for supporting students' textbooks, classroom work or self-study, and will also be a useful resource for scholars and professionals wishing to develop an understanding of the key features of the language. Grammar notes are numbered for ease of reference, and a section is included on how to use an Arabic dictionary, as well as helpful glossaries of Arabic and English linguistic terms and a useful bibliography. Clearly structured and systematically organised, this book is set to become the standard guide to the grammar of contemporary Arabic.

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.