The Role of Technology in Translation and Its Effect on the Translation Process - Essay Example

Table of Contents The Role of Translation Technology in Translation and it's Effects on Translation Process INTRODUCTION: The field of translation studies has seen tremendous changes in recent decades due in large part to the computer revolution. Machine translation (MT), for instance, received a lot of attention in the early days of computers when it was believed that machines would one day replace human translators. Hutchins and Somers (1992) and Arnold, Balkan, Humphreys, and Meijer (1994) provide a useful introduction and historical perspective on MT. The technology-centered approach in which many translators were first introduced to computers through MT caused conflict with technology visionaries. Early researchers (Weaver 1949; Booth 1953; Dostert in IBM 1954) were excited about MT for its technological potential. They marveled at the prospect of one day automating translation thereby providing an alternative to human translation. Translators, on the other hand, felt their craft was being undervalued and depreciated. They retaliated with feelings of fear and anxiety. As it became evident that machines would not soon take the place of human translators, attention shifted to forms of computer-assisted translation (CAT) technology. Kay (1980) and Belby (1982) in particular motivated research for computer aids to assist the translator. Books by Bowker (1998) and Somers (2003) contain articles about many aspects of computer technology for translation while Astemuhl (2001) and Bowker (2002), as well as parts of Sofer (2004), target the professional translator interested in acquiring the necessary technological skills. In addition to an increased focus on computer assistance for translators, the rise of globalization further increased the need for efficient computer support in view of making translation quicker and more cost efficient. One the best examples is Sprung (2000). The change in focus from replacing to assisting translators marked the beginning of a shift from technology-centered to human-centered applications in the translation industry. While a theoretical framework has been well been documented by psychologist Donald A. Norman (1998), truly human-centered technology has yet to come. Considering the changes the translation industry has experienced over the past 50 years, the objective of this paper is to asses the role of the technology in translation and its effect on translation process. In this context I will start by defining machine translation (MT) and computer-assisted translation (CAT), evaluate their impact on translation process and finally will discuss Toredo as a means to complete my translation project that I recently done. Computer-based translation technology roughly falls into two categories, Machine Translation (MT) and Computer Assisted Translation (CAT). Broadly speaking, MT is "the application of computers to the task of translation texts from one natural language to another". MT is mostly associated with stand-alone systems that seek to automate the entire translation process. CAT, on the other hand, are software programs designed to assist or aid the human translator by automating certain translation sub-processes such as terminology search and the reuse of previous translations. MT and CAT have no clear-cut boundary but rather belong to a continuum with varying levels of computer automation and human involvement. This process has been illustrated in the figure 1 below. Toady a translator working with word processing software and assessing various electronic resources such as online dictionaries may still be considered to producing 100% human translation. The key criterion is whether any part of the target text is automatically generated. There are many computer tools available to translators and almost as many ways to classifying them. Some tools consist of generic applications that have been adopted in many areas including the translation industry. Others focus specifically on the needs of translators and offer ways to run the business and support the translation process. When computer first entered the translation industry, there was much anticipation that they could one day replace human translators, particularly in scientific and technical fields. Hutchins and Somers (1992) placed translation tools into four levels of automation: fully automatic high quality translations (FAHQT), human-aided machine translation (HAMT), machine-aided human transition (MAHT), and traditional human translation (HT). Human involvement Mechanization Computer Assisted Translation Figure 1: Hutchin's and Somer's human and machine translation They placed FAHQT and HT at the far ends of the spectrum as unrealistic approaches to modern translation. On one hand, FAHQT is the pure machine translation with no human intervention envisioned by earlier academics such as Weaver (1949). Hutchins and Somers (1992) argued we can either have fully automatic translation or high quality translation, but cannot have both concurrently. Translation in the current age falls into two categories: MAHT and HAMT. Both approaches can be classified under the parent term computer-assisted translation. During MAHT the translator is responsible for the translation and technology is used as a resource tool when desired. Electronic mediums replace or complement tradition paper-based reference materials such as dictionaries, encyclopedias or terminology databases. Word processors with spelling and grammar correction capabilities allow greater flexibility for the finished product. On-line materials such as bilingual websites facilitate research. During MAHT the translator controls the technology, not the other way round. This approach is currently the most prevalent in the translation industry. During HAMT the computer is responsible for the translation and the translator plays a more passive role by assisting the machine. Human involvement can take place, during or after a computer processes a text. At the pre-editing stage, translators prepare the document for more accurate machine results. They may also be present during the actual translation process to correct problems or ambiguities a they arise. Lastly, they read the final results and correct errors that were not caught earlier. The computer is not in control during HAMT. 2. Machine Translation MT is generally understood to be the automatic translation of texts from one natural language to another by means of a computer system, with or without human involvement. MT is commercially important because human translation can be slow and expensive. It is also scientifically important, providing a testing ground for various ideas in linguistics, computer science, and artificial intelligence, and calling for an integrated approach because translation involves the application of the full range of human knowledge, ad crucial fact long known to translators but yet to gain wide recognition. The history of operational MT dates back to the mind-20th century, right after the invention of the modern digital computers and its successful application in code-breaking in World War II. In the Waver Memorandum of 1949, a landmark document that generated great enthusiasm for early MT research in the US and Europe, Warren Weaver compared translation to cryptography: one naturally wonders if the problem of translation could conceivably be treated as a problem in cryptography. When I look at an article I Russian, I say: "This is really written in English, but it has been coded I some strange symbols. I will now proceed to decode." (Weaver 1949). 2.1 Expectations of MT Even to this day the underestimation of the complexity of translation remains a negative factor affecting the translation profession and creating problems for quality control efforts on the part of translators. In order to find ways to improve the quality of MT output, it is important to understand why translation is difficult to automate. MT designers have always been realistic in the sense that they do not expect computers to do everything human translators do. Human translators often have to produce a text that is interesting, humorous, inspiring, persuasive, elegant, poetic, etc. based on the nature of the source text. MT systems, on the other hand, only handle the basic part other translation job: taking a pragmatic text in one language and producing a text in another language which contains the same information. MT systems are designed to handle technical documentation or general texts of an informative nature. MT output should contain the same information as the source text, but not necessarily the same aesthetic qualities as one would expect from a translation of Shakespearean plays. MT is not expected to play such a role. MT systems are after all devices for following rules. A brief examination of the basic MT architectures will illustrate the difficulty of reducing the complex task of translation to a set of rules that can be processed by computers. 2.2 Three MT approaches There are three traditional approaches to MT: direct, transfer and interlingua (Hutchins, 1986). The first, simplest and mot direct approach was adopted by some of the earliest MT systems, such as the Russian-English system jointly developed by IBM staff and MT researchers at Georgetown University and publicly demonstrated in 1954 (Hutchins 1994). There are no intermediate stages in the translation process, with words in the source text directly replaced by their 'equivalents' in the target language. The transfer approach, still adopted by many high-end MT systems today, involves three main stages: analysis, transfer, and synthesis or generation, with the transfer bridging the gap between the output of the source language parser and the input to the target language generator (Jurafsky & Martin 2000). In the first stage, the source-language representation is transferred both syntactically and lexically into a target-language tree. In the final stage, the target-language parsing tree is turned into the final, surface structure using target-language dictionary and grammar rules. On the other hand, Interlingua has only two stages: from the source text to the abstract representation of meaning called Interlingua and from Interlingua to the target text. The interlingua approach is evocative of an analogy between translation and reincarnation: just as the soul gets reincarnated in different bodies, the meaning of the source text gets reborn in various languages through translation. The ultimate question is whether there exists a soul that can be separated from the body, or with regard to translation, whether we can find an abstract representation of meaning that transcends all languages. To design a system of meaning representation that applies to all languages proves a daunting task, and the Interlingua model remains or more interest to research than to practical use (Austermuhl 2001). 3. Computer-Assisted Translation Through long overshadowed by MT, the idea of developing computer-based translation tools for translators, known as machine-assisted translation (MAT) or computer-assisted translation (CAT), dates back to the early 1960s. The ALPAC report of 1966, while dealing a heavy blow to MT research in the United States, encouraged support for the development of computer-based tools for translators such as text-related glossaries and terminological databases including terms in their sentence contexts (Hutchins 1998). Since then many people have advocated an integral approach to computer application in translation that takes into account the expertise and indispensability of professional translators. In discussing computer-based tools for translators, we tend to take word processing software for granted because it is so commonplace, yet it has fundamentally changed the way translators work and improved their productivity. Word processing gives translators the freedom to work at the sub-sentence level, so that they can start at whatever word or phrase that comes to mind and build the sentence from there. 3.1 Terminology Management An examination of the two main components of CAT packages, terminology management and translation memory, points to various factors, ranging from user-friendly design to equitable pricing scheme for translation services, that may contribute to the effective use of CAT tools by translators and translation companies. Terminology management serves to identify, extract, store, re-order, use and update significant terms with their translations in various languages. The primary function is to access specialized terms in the source language with standard "equivalents" in the target language. 3.2 Translation Memory Apart from terminology banks, one of the best resources for translators is past translation. If a previous translation offers an appropriate way to translate a word, phrase or expression in context, the translator should have the option to reuse that translation, partially or completely, rather than from scratch. Translation memory (TM), perhaps the single most important feature of CAT tools, allows the storage and re-use of matched pairs of source and target texts. The TM program can compare the new text with the database and retrieve identical segments for use in the new translation. 4. Trados as a Helpful Translation Tool For the current project I used trados which is composed of several different modules to help translators do their job providing them different necessary tools needed for the purpose. Trados provides its Trados WorkSpace to start the different components of trados suite in order to organize projects and files within projects. Trados provides extensive terminology solution through its Multiterm where the use can input term and its translation in several languages along with definitions. Besides, Trados also provides filters which are helpful for processing various formats such as FrameMaker, QuarkXpress etc. so that they can be translated in Word using its TWB and restored back to the original format (SDL Trados 2007). 5. Conclusion With the advent of digital computers, translation process has become much faster and cost effective. There are so many translation packages that help the professional as well as immature translators to do their job with ease and speed providing them helpful translation tools. References Arnold, D., Balken. L., Meijer, S., Humphreys, R. L. & Sadler, L. (1994) Machine Translation: An Introductory Guide. London: NCC Blackwell. Austermuhl, F. (2001). Electronic Tools for Translators. Manchester. St. Jerome Publishing. Baker, M. (1992). In Other Words. A Coursebook on Translation, London: Routledge. Bowker, L. (1998). Unity in Diversity: Current trends in translation studies. Manchester: St. Jerome Publishing. Bowker, L. (2002). Computer-Aided Translation Technology: A practical Introduction. Ottawa: University of Ottawa Press. Hutchins, J. & Somers, H.L. (1992). An Introduction to Machine Translation. London: Academic Press Jurafsky, D. & Martin, J.H. (2000). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Upper Saddle River, NJ: Prentice Hall. Kay, M. (1980). The Proper Place of Men and Machines in Language Translation. In S. Nirenburg, H. L. Somers & Y. Wilks (Eds.), Readings in Machine Translation (pp. 221-232). Cambridge, Mass: MIT Press. Sofer, M. (2004). The Translator's Handbook 2004 (5th rev. ed.). Rockville, Md.: Scheiber Publishing. Sprung, R.C., & Jaroniec. S. (2000). Translation into success: Cutting-edge strategies for going multilingual in a global age (Vol. II). Philadelphia: John Benjamins Publishing Company. Translation Memory (Trados 2007) retrieved from http://www.sdl.com/en/products/translation-memory.asp on January 4, 2007 Weaver, W. (1949). Translation. In Nirenburg, S., Somers, H. & Wilks, Y. (Eds.) (2003), Readings in Machine Translation (pp. 13-17). Cambridge, Massachusetts: the MIT Press. Read More