Machine translation (MT) is the area of computer science and applied linguistics dealing with the translation of human languages such as English and German. MT on the Internet has become an important tool by providing fast, economical and useful translations. With globalisation and expanding trade, demand for translation is set to grow. Translation Engines covers theoretical and practical aspects of MT, both classic and new, including: - Character sets and formatting languages - Translation memory - Linguistic and computational foundations - Basic computational linguistic techniques - Transfer and interlingua MT - Evaluation Software accompanies the text, providing readers with hands on experience of the main algorithms.

AMTA 2002: From Research to Real Users Ever since the showdown between Empiricists and Rationalists a decade ago at TMI 92, MT researchers have hotly pursued promising paradigms for MT, including da- driven approaches (e.g., statistical, example-based) and hybrids that integrate these with more traditional rule-based components. During the same period, commercial MT systems with standard transfer archit- tures have evolved along a parallel and almost unrelated track, increasing their cov- age (primarily through manual update of their lexicons, we assume) and achieving much broader acceptance and usage, principally through the medium of the Internet. Webpage translators have become commonplace; a number of online translation s- vices have appeared, including in their offerings both raw and postedited MT; and large corporations have been turning increasingly to MT to address the exigencies of global communication. Still, the output of the transfer-based systems employed in this expansion represents but a small drop in the ever-growing translation marketplace bucket.

Project Report from the year 2006 in the subject English Language and Literature Studies - Other, grade: 1,3, University of Frankfurt (Main) (Institut für England und Amerikastudien), course: Translation and Intercultural Communication, 26 entries in the bibliography, language: English, abstract: This paper will give a general overview of the venture that is machine translation with particular focus on linguistic aspects. It will display history of MT and will deal with some of the major issues in the realisation of MT like the difficulty of translating prepositions or integrating semantics, as well as the importance of real world knowledge. To illustrate these difficulties with examples on a basic level, a practice test with a moderately complex translation engine provided by Google has been carried out and will be explained. Finally, I am going to introduce three of the largest and most powerful translation machines currently in use. I will also give a brief over-view of methods of MT. The aim of this paper is to show that the realisation of the primal idea of machine translation in its original sense, which was to perform translation without human intervention (except during the construction phase of the system), is still markedly far away at present and machines are still unlikely to take over the jobs of human translators.

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.

Machine Translation and the Information Soup! Over the past fty years, machine translation has grown from a tantalizing dream to a respectable and stable scienti c-linguistic enterprise, with users, c- mercial systems, university research, and government participation. But until very recently, MT has been performed as a relatively distinct operation, so- what isolated from other text processing. Today, this situation is changing rapidly. The explosive growth of the Web has brought multilingual text into the reach of nearly everyone with a computer. We live in a soup of information, an increasingly multilingual bouillabaisse. And to partake of this soup, we can use MT systems together with more and more tools and language processing technologies|information retrieval engines, - tomated text summarizers, and multimodal and multilingual displays. Though some of them may still be rather experimental, and though they may not quite t together well yet, it is clear that the future will o er text manipulation systems that contain all these functions, seamlessly interconnected in various ways.

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.