Vanessa Enríquez Raído, Barcelona - Frank Austermühl, Mainz/Germersheim

Transcription

1 Vanessa Enríquez Raído, Barcelona - Frank Austermühl, Mainz/Germersheim Translation, Localization, and Technology Current Developments 1 1 Introduction The phenomenon globalization and the advent of the information age have brought about considerable change within the discipline of translation. With regard to their impact on the use of information and communication technology (ICT) solutions by translation professionals and scholars, these changes constitute a paradigm shift (see Austermühl 2001a). Whether the same holds true for the translation discipline as such, that is, whether the localization paradigm can be regarded as a new, overarching approach to translation studies, will be an interesting development to watch. In any case, and regardless of skeptical voices from the academic world, translation has become part of a multi-billion dollar business the so-called GILT industry (globalization, internationalization, localization, translation). It is our goal in this article to introduce the reader to the state of the art of the manifold forms of ICT usage in the world of professional translation and localization. In doing so, we are following a thoroughly process-based approach to the analysis, evaluation, and design of electronic tools for translators (see Austermühl 2001b) and other related applications of localization technology (see Esselink 2000, Sprung 2000). This approach implies that the design and use of translation- and localization-oriented ICT solutions are subordinated to the demand for information and automation that are arising during the individual phases of the translation and localization processes. This approach also implies a clear hierarchy that places the professional in charge of the tools, making the latter means for increasing not only the productivity of the translation process but also the quality of the translation product. In general, we will distinguish between two separate, yet closely interconnected sub-processes, each requiring its own set of task-specific tools. The first of these domains comprises the ''classical'' three-step translation model of source text reception, information transfer, and target text formulation. The network- and computer-based resources used during this core translation process aim at providing the translator with the linguistic, encyclopedic, and cultural information necessary to successfully perform his or her task. Since we consider translation to be an utterly knowledgebased activity (see Stolze 1992), these "translator tools" will ideally serve to enhance the translators' hermeneutic abilities, thus allowing them to unfold their full, creative potential. 1 The authors would like to thank the Ministerio de Ciencia y Tecnología, Madrid, and FEDER for funding research project BFF of which the current work is a part. 1

2 This ideal situation of a translator's freedom, however, is in many cases torpedoed and restricted by a second group of electronic tools. These applications, which we will call ''localizer tools,'' aim primarily at streamlining the business process of translation, especially with regard to larger, repetitive translation tasks and projects. Although from the point of view of a human translator it is tempting to characterize these tools (primarily translation memories or localization tools) as merely productivity-enhancing, their impact on the improvement of translation quality, especially with regard to terminological and phraseological consistency, should not be ignored. Figure 1 reflects the approach taken in this article with regard to the categories of translator and localizer tools. Translation and Localization Technology Localizer / Productivity Tools Translator / Knowledge Tools DTP Tools Term Extractors, Term Bases Term Bases (Glossaries) Encyclopaedias Quality Assurance Tools Translation Memories Back Ends Translation Memories Front Ends Dictionaries Project Management Tools Localization Tools Back Ends Localization Tools Front Ends Digital Archives Workflow Systems DIY Corpora Content / Globalization Management Systems Concordancers Machine Translation Specialized Websites and Newsgroups Internationalization Tools Multilingual Knowledge Management Figure 1: A Typology of Translation and Localization Technology In the following we will be focusing on the various translator tools, on translation memory and localization solutions, which are used by translators and localizers alike, and on machine translation systems. The other tools listed are primarily used by larger translation agencies to help optimize the localization workflow and, as in the case of multilingual content management systems, to speed up the actualization of multilingual documentation or websites. 2

3 As this typology shows, the automation of the process increases from right to left. The model also shows the overlap in terminology database, translation memory (TM) and, to a lesser extent, localization (L10N) tool use by translators and localizers. The TM and L10N solutions available for translators and localizers do vary however with regard to the number of available features. Software used by freelance translators oftentimes offers only part of the functionality available to localizers. These customized applications have become known as 'light' or 'front-end' solutions. It should be noted that while our distinction between 'translator tools' and 'localizer tools' serves a theoretical and didactic purpose, the processes involving these tools and their individual advantages and disadvantages cannot and should not be seen as separate, and the close interconnection of translation as the transfer of knowledge across cultural and linguistic borders and translation as part of a larger business process must not be neglected. In our discussion of translation and localization technology and its impact on translation professionals, students, trainers, and scholars, we will be focusing primarily on the area of software localization. It is in this area of international technical communication, i.e. the adaptation of computer applications developed in and for a given local market to the cultural, economic, political, and legal conditions (the so-called locales) of a given target market, in which the dominance of both the English language and ICT solutions is most striking. Despite the focus on software localization, however, it is important to stress that the use of translator and localizer tools is not at all restricted to the ICT sector but today represent a truly universal phenomenon, which, for example, with regard to the localization of website content or the creation of multilingual product documentation, expands across all industries. By concentrating our analysis on both tools and skills (see Enríquez Raído 2000) involved in the many sub-processes of translation and localization, and by linking them to a typology of L10N texts, we also aim at providing a sound basis for the development of curricular modules for the training of translators. Customized modules on localization and technology are still absent in the majority of translation programs today, and we see our article as an attempt to contribute to the modernization and standardization of curricular designs in these fields. 2 A Changed Profession Despite the dominance of English as the global lingua franca, the demand for translation services is rising steadily. In 1997, the total turnover of the translation markets of 18 member states of the European Union and the European Economic Area (EEA) was estimated to be 3.75 billion euros with software, audio-visual, and multimedia translations constituting 20 % of the total turnover. According to a 1998 study by Allied Business Intelligence (ABI) the global translation market was expected to grow from over US $10.4 billion in 1999 to close to $17.2 billion in 2003 with software 3

4 and website localization being the largest contributors to this change. According to the ABI study, the global turnover for software localization services will increase to between 4.8 and 6.3 billion US dollars in Localization of software created in the United States accounts for eighty percent of these amounts ( The growing demand for translation services and the business opportunities provided by this development have brought about significant changes in a generally traditional field. Today, translators find themselves in a diversified, automated, and highly professional working environment. As experts for intercultural technical communication, modern translators often double as technical writers, lexicographers, software testers, or cultural consultants (see Austermühl 2001b). In any of these fields, they will be confronted with the necessity of applying any number of ICT solutions. Translators who for many years have led professional lives comparable to Spitzweg's "Poor Poet" have become part of the cut-throat corporate world. This world is a strictly hierarchical one, with the translation food chain being made up of four main species: at the top there are the clients, large international corporations like Microsoft or SAP or Telefonica. These delegate to and communicate with internationally, multidirectionally operating MLVs, multi-language vendors, of which there are only but a handful of big ones left (i.e. Lionbridge, SDL International, and Bowne Global Solutions). Next are the SLVs, single-language vendors, who provide translation services from various source languages into one single target language. Last in this chain, translation's 'bottom feeders' so to speak, are the individual translators, the majority of them working as freelancers. These four groups constitute a kind of multi-level translation conveyor belt, which is based on an elaborated, multi-component ICT infrastructure. 3 Translation and Localization Technology The spectrum of electronic translation tools available today covers a wide range of state-of-the-art computer applications ranging from spell checkers to machine-translation systems, from wordprocessing software to terminological databases, from electronic encyclopedias to online dictionaries, from HTML editors to software-localization tools. Electronic newspaper archives, professional mailing lists, translation memories, content management systems, speech recognition software, etc. all become valuable translation resources if used in the right way. While there have been many proposals for categorizing the confusing number of tools (e.g. Melby 1982 and 1998 or Hutchins, Somers 1992), most translation technology models do not allow for an in-depth understanding of the efficient and practical use of ICT in professional translation activities. They do not differentiate between the specific tasks supported by individual tools, neglecting their positions within the localization process as well as the skills needed for their effective application. In order to 4

5 achieve that understanding, a different approach is needed, an approach that sees translator and localizer tools as an integral part of a larger multilingual communication process. 3.1 Translator Tools vs. Localizer Tools With our general distinction between translator tools and localizer tools (see figure 1) we have already laid down a general typology of translation and localization technology. This approach sees translation as an integral part of localization, and accepts the notion that localization is more than just translation (see Fry 2001). At the same time, the model reflects our conviction that most professional translators will usually not be actively involved with many of the localizer tools mentioned in the model, not to speak of internationalization tools (see below) or globalization management systems (GMS) that support the almost simultaneous publication and updating of multilingual documents. Nevertheless, translators, working freelance or in-house, are many times confronted with the consequences of the automation of the industry. They no longer receive simple source texts but expansive localization kits containing document files in any kind of format, projectspecific translation memories, and multilingual glossaries. The use of translation memory applications is the professional standard today, and front-end solutions for localization tools are also starting to reach the translator's desktop. We will therefore deal with both kinds of technology: translator tools and localizer tools, thereby highlighting the interrelations between the two categories, which are most notable with regard to translation memory systems. This approach also expresses our view that while professionals from the field of translation and localization will at any given time usually work with the tools from their respective category (with, of course, the option of changing between these professional domains), translation students and trainers, as well as scholars of translation studies must take both areas into consideration. 3.2 Translator Tools Effective use of translation technology starts from the translator's point of view. In order to avoid a translational 'wag-the-dog' syndrome, the translator has to determine what types of translation technology are needed at what stages of the translation process in order to optimize his or her professional performance. As a knowledge-based activity within a highly specialized and fragmented international communication environment, translation relies heavily on the availability of information resources. In this regard, electronic translation tools function mostly as artificial knowledge bases providing the translator with world and expert knowledge. 5

6 Within each of the three main phases of the translation process -- reception, transfer, and formulation -- different sub-competencies are demanded by translators, and the tools used to support them have to offer specific features and contents. The following chart illustrates the individual phases and the categories of tools suitable at each stage. (For a more detailed discussion of the process-oriented approach to electronic tools for translators see Austermühl 2001b.) Translation - The Tools Source Culture Target Culture ST Map Transfer Culturally-Sensitive Information Systems TT Map Reception Terminology Databases Reception Dictionaries Electronic Encylopaedia Knowledge Databases Text Analysis Tools Terminology Databases Production Dictionaries Electronic Archives DIY Corpora Translation Archives Formulation Source Text (ST) Direct Transfer Translation Memories, Localization Tools, Machine Translation Target Text (TT) Figure 2: Electronic Translation Tools and The Translation Process (Source: Austermühl 2001b) During the reception phase, the source text is analyzed, primarily with regard to textual aspects like its function or target group (see Nord 1997) and to identify the translator's information needs for the particular tasks ahead (see Hönig 1998). This first step can also comprise a statistical text analysis that can be assisted by electronic tools such as Word Cruncher, in order to filter the special terminology used in the text. This results in type-token lists, and KWIC (key word in context) concordances. These lists, which show the dominant terms and their typical collocations of the source text, can then used by translators especially those working in teams to ensure terminological consistency throughout the translation. The KWIC concordances can be directly imported into terminological databases. Some translation memory systems and localization tools (see below) offer a terminology extraction function that automates the identification of projectrelated terminology, but does not show the terms in their immediate context. During the reception phase, a translator can use electronic encyclopedias, digital knowledge databases or information retrieval systems or can contact domain experts through online newsgroups or mailing lists in order to retrieve missing background knowledge, allowing him or her to combine text, domain, and world knowledge to fully understand the content of the source text. In 6

7 the graph this abstract, culturally-influenced understanding is represented by a so-called map. In addition, a translator can use general or specialized electronic dictionaries or multilingual terminology databases to decode the linguistic information of the source text. This kind of "reception" dictionary needs to provide a high degree of paradigmatic information, like synonyms, antonyms, and hyperonyms, to facilitate the understanding of the text-internal knowledge by positioning a given term in its lexical context. The transfer phase, i.e. the adaptation of the source text information to the context of the target text culture is uniquely translational. Neither readers nor writers share this phase with the translator. It requires deep cross-cultural understanding and strong intercultural communication skills. The tools needed during this stage of the translation process need to offer a high degree of intercultural knowledge, while at the same time providing the translator with a comparative analysis of the cultures affected by the translation project. Resources in this field are still rare, and special kinds of translator dictionaries or culturally-sensitive terminology databases providing a thorough combination and networking of linguistic, encyclopedic and intercultural knowledge have to be designed to assist translators during the transfer phase. In this regard, hypermedia systems seem to be a valid solution (see Holderbaum, Kornelius 1999 and Albrecht, Austermühl, Kornelius 1999). One of their advantages is the ability to incorporate not only textual information but also audio and video sequences thereby giving lexicographers the chance to include non-verbal aspects of intercultural communication into their works. Finally, the formulation phase confronts the translator with challenges regarding the production of the target language text. Here again, the use of dictionaries and terminology databases can assist the translator quite efficiently. The information contained in those resources needs to offer support especially with regard to the syntagmatic relations of terms, as can be found in many style guides or in collocation dictionaries. Dictionaries providing such information become valuable production dictionaries (see Kornelius 1995). In addition, the translator can turn to text archives available on CD-ROM or over the Internet for the verification of tentative translation solutions in the target language. Among the criteria these text archives have to meet are the provision of Boolean operators (AND, OR and NOT) and proximity operators (like NEAR BY, FOLLOWED BY or ADJACENT). The latter are even more important when it comes to locating collocations and determining the collocational range of any given combination. Using the vast resources of the Internet, translators can also create their own specialized corpora (do-it-yourself corpora) and use text retrieval systems or customized search engines to access the information stored on their own PCs. In addition to existing or self-created monolingual text corpora, translators can also access non-aligned bilingual text archives that store original texts along with their translations. Since these tools are usually used to show a key word and its target language equivalent in its context, they are 7

8 sometimes also referred to as bilingual concordancers (see section below on translation memories and translation support software). The tools mentioned above all aim at providing the translator with information needed during the reception, transfer, and production phase of the translation process. Independent of their particular role within that process, they all seek to liberate the translator from the restraints of the source text by enabling him or her to fully understand the meaning of the original, to adapt its contents to the target culture, and to self-consciously produce an independent text that functions as an original in the target culture. It should be noted at this point that terminological databases that serve as reservoirs for multilingual units of encyclopedic, linguistic, cultural, translational, and administrative information can serve as ideal unifying platforms for the different types of data supporting the translators during the entire process. Many translation suites, be they translation memory systems, localization tools, or a combination thereof, do offer terminology modules. Maintaining powerful terminological databases, however, is a work- and time-intensive task, and here as well software solutions need to mirror the actual routines of translation-oriented terminography. The above types of translator tools can be seen as technology solutions that ideally empower the translator to unleash his or her full creative potential. While translation memories (including their terminology features) as well as some components of localization tools and, in rare cases, MT applications, are being used by translators as well, we do not think that they serve to promote the hermeneutic potential and the empowerment of translators. And while accepting their advantages in assuring above all phraseological and terminological consistency and thus translation quality, we primarily characterize them as leverage or productivity tools aimed at an automated direct transfer of source text fragments into the target language, and as solutions for dealing with the specific data formats of software-related texts. We recognize, however, the fact that TMs and L10N tools are not only valuable tools for localization project managers but are also widely used in the form of special front-end versions by professional translators, and that the need for adequate training in this field is considerable. 3.3 Localizer Tools The above model calls for individual use of electronic translation tools with regard to the specific sub-processes of the translation process. However, in the past five to ten years, the language industry has spent enormous amounts of money creating and marketing products designed to automate the process of translation (almost) completely. The advent of these tools is also a reaction to the need to streamline and standardize the localization process, to deal with ever tighter deadlines, to process text types of growing technical complexity, and to meet the high demand for 8

9 and decreasing turnover rate of website L10N. In the following, we will be discussing these applications, focusing on translation memories, software localization tools, and to a lesser extent, machine translation systems Translation Memory Systems Translation memory systems (TMS) like Atril's Déjà Vu, Star's Transit, IBM's Translation Manager, SDL's SDLX, Champollion's Wordfast, or Trados' Translator's Workbench are databases that allow for the parallel storage of source and target text segments on a sentence, phrase or word level. These segments can be retrieved and then used for a new translation project. Special software identifies whether the new text to be translated contains passages that are already stored in the translation memory (TM). The translations corresponding to the segments found in the TM database are then offered as translation proposals for the new text. Since phrases do not always look exactly alike (i.e. they are not perfect matches), translation memory software allows for so-called fuzzy matching. This technique searches the database for segments that are very similar to the original source text. This would for example work if one segment stored in the TM reads "Click the OK button" and another segment would read "Click the Next button". The user can select the degree of 'fuzziness', i.e. the percentage of similarity between old and new segments acceptable in this pretranslation process. Translation memories can be built either during or after the translation process. In the latter case, a process called alignment is used to match the text segments of the source text with their translations in the target text. This means that translations that have been produced prior to the purchase of a translation memory system can be made available as well. Some TMS, like Transit or Déjà Vu provide proprietary text editors, while others like Translator's Workbench incorporate their functionality directly into an existing word processor, thus enabling the translator to work within a familiar environment. Converters support the import and export of files into these proprietary formats. Special characters, so-called tags, guarantee that after the text has been translated using a TMS the original format will be restored. Most TMs provide the same basic features, such as word processing (including spell and grammar checking) in multiple, parallel windows; access to and management of translation memories; alignment software; terminology extraction, recognition, and management; file format converters; layout monitoring; support for single- as well as double-byte languages; and others. Some TMS also allow for the integration of machine translation solutions. Most TM applications, or TM suites, include a terminology management module that is directly connected with both, the translation memory and the word processor/editor. The most commonlyused applications are MultiTerm (Trados), TermBase (SDL), TermStar (Star), TermWatch (Atril), 9

10 TransLexis (IBM). In addition, some TM providers are now enhancing the features of their solutions (or suites) by adding editors or converters to handle resource and binary files and thereby becoming software localization tools (see below) Selecting TM Systems The decision to use TM technology and the selection of a specific TM systems naturally depend on the needs of the individual user. The following list of criteria can be seen as a general guideline for the selection of TM systems: Text types: As in the case of machine translation (MT) systems (see below), the degree of automation and the increase in productivity achieved by TMs depends on the type of the text to be translated. The text types most suitable for TM use, that is the ones promising the highest degree of leverage, are technical documents like specifications, user manuals, or online help files that all have fairly standardized and repetitive linguistic characteristics. Re-usability of content: Naturally, the efficiency of TMs depends of the number of recurrent segments within the source text. With regard to repetitive contents, two types can be differentiated: internal repetitions, i.e. recurrent text fragments within the same source texts, and external repetitions, i.e. text fragments that appear in texts other than the current source text. The re-usability of content is closely related to the stylistic, phraseological, and terminological consistency of the source texts. Therefore, like in MT systems, the standardization (or control) of the original production of the source text document can contribute to the efficiency of TM systems. Frequency of updates: TM systems have their origins within the realm of software localization where annual updates (and more frequent intermediate patches) are common and for which the accompanying texts (e.g. manuals, online help files) need to be updated regularly as well. Given the fact that these updates will usually contain only slight modifications, TM solutions will considerably speed up the localizing process. Type of format: Technical documentation is produced using a large variety of word processing, desktop publishing, web editing, or programming applications that all produce different file formats. To be processed by TMs most of these file formats have to be converted, and while the leading TM providers all generally support RTF, DOC, HTML, XML and various DTP files, the handling of more specific formats like resources files (RC) or binaries (EXE, DLL) cannot yet be considered a standard TM feature. Volume: Text volume is another key factor in deciding when to use a translation memory. Especially for freelancers, the decision must be made on the basis of the initial costs of purchasing the tool and the potential savings that will be made when using the tool. Utilities like the 10

11 Cost/Benefit Estimator (available at help determine the economic viability of using a translation memory tool. Other issues influencing the selection of a TM suite are the price of the system (including costs for training and technical support), customer preferences, or, in the case of freelancers, the demands of translation agencies, and the compliance of the product with the so-called TMX standard (see Briggs 2002). The diversity among modern TM systems has led to a great variety of oftentimes incompatible TM file and database formats. In order to facilitate the exchange of existing TMs among proprietary systems, software developers, tool providers, and translation services created the XML-based TMX and TBX standards that provided the basis for the exchange of translation memories and terminology databases, respectively. The initiative was headed by a special interest group of the Localization Industry Standards Association (LISA) called OSCAR (Open Standards for Container/ Content Allowing Re-use). Two more standards worth mentioning are the ones created under the umbrellas of OpenTag ( and OASIS ( In conclusion, we would like to sum up the main characteristics and advantages of TM systems: Given the fact that technical documentation in general tends to be redundant, the use of TMs eliminates the need for repetitive translations of regularly recurrent textual segments. This refers to repetitions of the same or similar source text units within the same text (internal repetitions) or repetitions within a corpus of previously translated texts (external repetitions). The automatic recognition of previously translated segments increases the stylistic, phraseological, and terminological consistency of the target texts, which constitutes a major quality improvement. The elimination of repetitive task leads to faster turn-around times, productivity increases, and lower costs, and at the same time free the translator from time-consuming, boring, and error-prone tasks. Project management functions available within TM tools provide, for example, statistical information about translated segments and thus allow for the better planning and monitoring of localization processes. Translation memories can be used over local or global networks (see Bugel-Shunra 2002), which speeds up team-based translation projects, and helps to secure consistency among translations produced at remote, yet interconnected sites. Despite these undisputed advantages, TM usage also includes to a number of inconveniences, especially from the point of view of individual translators. Among the complaints from the translator community about the negative consequences of TMs are the rigidity of source text 11

12 structures, the dominance of the sentence or sub-sentence phrases as primary translation units, incompatibilities within one TM or between TM and term bases contents, faulty, yet untouchable TM segments, the lack of creativity for the translator as autonomous text producer, the lack of cotext and context for the segments to be translated, and, last but not least, the lack of motivation or freedom to go beyond the simplistic source text structures and the preexisting translations imposed upon the translator by the TM system. Another problem with regard to the use of translation memories is the question of copyright and intellectual ownership of the translations that form part of the TM. Given the dangers of a snowball effect of translation errors embedded in TMs, the assurance of the quality of segments stored in TMs (for source texts as well as for target texts) and the consistency of TM and term bases contents become essential for the overall quality of any translation project. Therefore, TM systems must provide for the easy manipulation and updating of existing TMs, including the automatic update and replacement of new or modified terminology. This quality maintenance is directly related with the reliability of a TM and thus with the quality of the work produced using a TM system New Developments in TM Systems The latest attempt to optimize TM systems is represented by so-called Translation Support Software (TSS), which bases the recognition of previously translated segments on a more flexible system of rules (Hunt 2002). Using natural language processing (NLP) strategies found in modern search engines, TSS take into account the existence of conjugations, singular or plural forms and other syntactic elements. This recognition of typical linguistic patterns within previously translated texts represents the main difference between TSS and traditional TM systems, which are based upon a statistical analysis, i.e. the comparing of strings and counting of characters. The following example (Macklovitch, Russell 2000) shows the differences between a string-based approach and one that employs NLP techniques. (1) The wild child is destroying his new toy. (2) The wild chief is destroying his new tool. (3) The wild children are destroying their new toy. As Macklovitch and Russell point out, traditional TM systems would judge the first sentence as being more similar to the second sentence than to the third, since it only differs in four characters from the first sentence as compared to nine in the third sentence. However, an NLP-based TSS would be able to recognize the plural forms in the third sentence and therefore judge its similarity with the source sentence as higher than that of the second sentence. 12

13 Another characteristic of TSS designs is that they do not align source and target texts on a phrase or sentence level but use a key word or a combination of key words from a new source text to access stored sentences containing the same word. To speed up the process of finding key words, every word in a TSS is indexed. In is sense they very much work like concordance programs (or the concordance features integrated in some TM systems) and can be seen as a combination of translation memory solutions and corpus-based approaches to translation tools. Example for TSS solutions are TermSeek's Translator's Intuition ( and the University of Montreal's TransSearch ( Software Localization Tools Before software localization is explained, it is necessary to briefly to introduce the concepts of globalization, internationalization, and localization. Globalization (G11N) in general refers to the "process of worldwide economic, political, technological, and social integration" (Fry 2001: 34). In a more limited way, G11N is seen as a series of deliberate strategic business decisions to guarantee the global readiness and marketability of products. Internationalization (I18N) refers to the technical measures taken to facilitate the localization of products. For example, ensuring that steering wheels for cars can be mounted either on the left or on the right side depending on the regulations of the target market would be part of the internationalization. Actually putting the wheel on the left or right side would be part of the product's localization. With regard to the software industry, internationalization includes, among others, taking into account cultural differences like date formats or, with regard to financial software, different tax codes. Proper internationalization allows for a product's easy adaptation to any given local market without the need to change the general design of the product. Some of the linguistic and cultural idiosyncrasies of software-related texts are, for example, character codification, keyboard layouts, writing directions, varying text lengths, as well as different norms and formats for dates, times, calendars, numbers, postal codes, currencies, temperatures, paper sizes, colors, etc. Finally, localization (L10N),, is the process of adapting a product to the cultural, linguistic, social, and legal norms of the target market. Although localization is not restricted to computer application products, the software market is certainly an important sector for translation and an area in which there is a strong demand for the service of translators (or localizers). Translation is an important part of the localization process. However, as the following model of a typical localization project (taken from Esselink 2000) shows, it is only one step in a larger business process: 1. Analysis of Received Material 2. Scheduling and Budgeting 13

14 3. Glossary Translation or Terminology Setup 4. Preparation of Localization Kit 5. Translation of Software 6. Translation of Help and Documentation 7. Processing Updates 8. Testing of Software 9. Testing of Help and DTP of Documentation 10. Product QA and Delivery 11. Post-mortem with Client Localization Text Types Computer applications include a great number of electronic and print texts that need to be translated as part of the product's localization. The typology displayed in figure 3 is a tentative attempt at categorizing the many different texts that occur within the context of software products that need to be translated as part of the product's localization. Figure 3: A Typology of L10N Texts Translation memory systems will mostly be used for the translation of documentation text types like product manuals or online help systems. In addition to these texts, the localization of a product naturally needs to include the translation of the program per se as well, i.e. the various texts constituting the user interface. Since these UI texts menus, controls, messages, etc. are embedded 14

15 as strings in the program's source code, translatable texts needs to be separated from nontranslatable texts in order to guarantee the functioning of the program. UI texts are stored in different files that require different technical and methodological approaches to their translation. With regard to a typical Windows application, the texts come in two basic formats: As resource files (typical extensions are RC or DLG): These are text-only files that include all the localizable components described above. Resource files are converted (compiled) into programs using a so-called resource compiler. They can be translated using a simple text editor or a word processor. Since resource files contain UI texts as well as program code, the text to be translated is put into quotation marks. Text not identified in that way is not to be translated. Since both, UI texts and program code all form part of the same text file, visual identification of the text strings to be translate is not always easy and program code might be deleted by mistake. Therefore, so-called resource editors such as Microsoft Developer Studio are also used to translate resource files. These applications have the advantage of separating program code from translatable texts, thus making UI texts easier to identify while at the same time reducing the risk of program code deletion. As program files (executable or binary files with typical extensions being EXE or DLL): The UI texts contained in these files are translated either by using a resource editor, e.g. Microsoft App Studio, or with the aid of software localization tools like Catalyst or Passolo. The main advantage of this processing form is that through WYSIWYG the translations are immediately displayed within the actual software environment, for example on a command button or within a dialog box. In doing so, the translator or the responsible project manager can immediately check whether, for example, the length of the translated segment fits into the available screen space Common L10N Tool Features Software localization tools combine a variety of translation- and localization-related applications. These can be summed up as follows: Dialog box and menu editing in WYSIWYG mode: As mentioned above, this displaying technique enables the translators to directly work within the program and to immediately see the results of their work within the localized software environment. Software engineering feature: Among some of the feature included in this category are so-called pseudo translators that allow the user to simulate the translation of the project files, thus detecting possible L10N errors that might cause problems and that have been overlooked during the previous internationalization process. For example, Catalyst's Pseudo Translate Expert allows to simulate the expansion of a given text string (by up to 100%), which enables the user to view how the user interface, e.g. a command button texts, might be affected by differences in the length of source and 15

16 target text. Furthermore, this kind of L10N pre-test can also be used to check if a product is compatible with special characters that occur in the target language texts. Leverage features: These TM features facilitate the re-use of translations from a previous version of a product. Within some L10N tools the user has to provide previously translated versions and glossaries as reference material. As in TMS, identical or similar text strings are than extracted according to the user-defined fuzzy match value (see above) and the translations are copied into the new project. Other L10N tools integrate existing TM solutions, or, as in the case of Trados, enhance their TM suites by L10N features. In addition, some L10N tools allow not only the leveraging of text but also of dialog box co-ordinates (i.e. the size and position of a dialog in the application at runtime), thus reducing resizing tasks (i.e. those involving adapting the size and/or position after translation). Terminology extraction and glossary management functions: Using an automatic terminology extraction feature, L10N tools allow to either create a glossary a priori containing the relevant specialized terms of a source text or to create a bilingual glossary a posteriori containing the terms of the source text and their target text equivalents to assure terminological consistency for future versions. In addition, L10N tools, like TM suites, usually contain a terminology database whose designs can vary from simple three-column tables to full-fledged terminological management system. Validation features: These are quality-assurance mechanisms that allow for the automatic identification of localization errors. These include, among others, identification of differences in the number of hotkeys (i.e. accelerator keys used to activate commands by pressing it in combination with the ALT key) between source and target text, duplicated hotkeys in menus and dialog boxes, mismatched empty strings, invalid ampersand positions (which are used to identify the hotkeys), etc. The validation results are usually displayed in a separate window. Selecting a validation error immediately opens the object containing the error so that it can be corrected. Project management features: These features help simplify the co-ordination of a L10N project by, for example, offering the possibility of combining many different files into one archive, thus making it easier to keep track of the single files, or the sub-division of the entire project into smaller projects, which allows for distributed translation projects. Other project management options include features to monitor the progress of individual tasks, or the automatic generation of word counts on different file types. Also, a statistical report can be generated to document the current project status. 16

17 Finally, it might be added that most L10N tools offer spelling and grammar checkers as well as a non-compiling feature allowing the user to store the translated files directly in their original, binary format. 3.3 Machine Translation The advent of the Internet and the rising need to translate both websites and communication has renewed the interest in MT solutions. The AltaVista search engine, for example, is offering the automatic translation of web pages using Systran's MT technology. In addition, WWW-based MT portals like Cyber Paperboy, Foreignword, Translatum or Word2Word now offer 24/7 translation services, and MT powered websites like Babelfish automatically translate texts received over the Internet or communicated via mobile phones. 2 These developments as well as the evolving cooperation between TM and L10N tool providers and MT developers lead us to include a brief introduction 3 to MT into the discussion of translation technology. The basic idea of machine translation (MT) is that of Star Trek's universal translator or a mechanized version of Douglas Adams' Babel Fish a black box that coverts the source language input into a (perfect) target language output without any human interaction. After spending a great deal of money, MT systems developer gave up the idea of Fully Automatic High-Quality Translation (FAHQT) and focused instead on using MT for the translation of texts covering a highly-restricted encyclopaedic and terminological field and consisting of very simple sentence structures Areas of MT Usage and Quality Demands As far as strategies for optimizing MT output are concerned, the definition of the user's quality demands is of fundamental importance. There are two standard positions: information-only quality and professional quality. Some MT output is "intended for information-only skimming by experts able to visualize the context and discount errors" (Gross 1992: 98). If information-only quality (so-called "gisting") is demanded, raw MT output with little or entirely without post-editing is sufficient. This low-quality demand is fulfilled when the translation is readable and comprehensible. Melby (1995: 37) calls this 'indicative translation.' Grammatical errors and clumsy styles are accepted, provided the message of the target text is clear. The translation may also help the user decide whether the text is relevant enough to be passed on to a human translator. 2 For a comprehensive list of these free service see 3 For more detailed discussions of MT see for example Arnold et al and Hutchins and Somers

18 Pre-editing (see below) is of essential importance when the user requires professional target text quality, as is the case with texts intended for publication or for other broad dissemination. How much post-editing or revising is required in order to yield 'full-dress translations' (Gross 1992: 98) largely depends on the quality of the raw translation. Professional quality is often aspired to when (high-end) MT software is used, for example in multinational companies for the translation of product documentation. In most cases professional translators are employed to do the post-editing work Improving MT Performance Strategies for optimizing the quality of MT texts include updating the system's dictionaries, preediting the source text, post-editing (revising) the target text, and human-machine interaction during the translation process. These measures do not exclude each other. Pre-editing and post-editing refer to the input or output texts, whereas the other measures influence the working of the program itself. Since complex syntactic structures, idioms, ellipses, and anaphora are likely to cause problems for the MT system, pre-editing includes, for example, avoiding idiomatic expressions and relative pronouns, breaking up long sentences into shorter ones (one idea per sentence), keep to the typical word order subject verb object, using active instead of passive voice, not splitting separable English verbs (e.g. look up), etc. Pre-editing also involves the use of unique terminology and the identification of text that is to remain unchanged (e.g. proper names, addresses). One important approach to writing rules aimed at improving MT quality is that of controlled language, which can be defined as "a form of language usage restricted by grammar and vocabulary rules" (Arnold et al. 1994: 156). It is in fact an extensive form of pre-editing, even though the concept of controlled language was not specifically developed for MT (see Akis, Sisson 2002). A more general form of restrained input might be the 'special languages' used in particular technical fields. Such languages are characterized by carefully defined lexical items and by the fact that certain syntactic structures are used more frequently than others--in technical manuals, for example, instructional forms are predominant. This means that the MT system can be adapted to those structures. System designers make use of such advantages when developing sub language systems adapted to "a particular syntax, semantics, and pragmatics within a well-defined domain" (Melby 1995:39). The best-known example of this is the Météo system used in Canada for the translation of weather bulletins. Post-editing is carried out after the translation process, as the name indicates. It refers to the correction of the target text, i.e. the raw translation generated by the MT system. Whether postediting is conducted, and to what extent, largely depends on the quality required by the user. 18

19 Wilss (1988: 183) argues that the tasks of pre-editing and post-editing should be put in the hands of professional translators who are aware of the limitations of MT, since without such professional intervention the process is very time-consuming and inefficient. The general performance of an MT system can be improved either by updating the system's dictionaries (before translation) or by interacting with the system (during translation). The users of an MT system may adapt the dictionary component to their particular needs. This involves adding information, i.e. entering missing terminological expressions from the user's field, or modifying existing entries. Depending on the structure of the dictionary, morphological, semantic and phraseological information can be added to the entry. The complexity of the dictionary should thus be taken into account when evaluating an MT system. Some MT systems have an interactive mode that enables the program to consult the user when it encounters problems it cannot solve on its own. The system pauses during the translation process, for example when it cannot resolve syntactic or semantic ambiguities in source text analysis or when it cannot decide on one target language equivalent or the other. This means that errors can be avoided in the analysis stage. 4 Conclusion The advent of the information age has sustainably altered the profession of translation, especially with regard to the type of electronic tools used, the type of texts translated, and the types of skills needed by today's translators and localizers. A process-oriented approach that generally differentiates between knowledge tools (translator tools) and productivity or leverage tools (localizer tools) will help to improve the design, application, and evaluation of translation tools. In this regard, a general distinction between knowledge-providing translator tools aiming at empowering the translator and localizer tools primarily serving to automate the localization process and to increase productivity is helpful. However, terminology extractors, terminology databases, and translation memories are important means to guaranteeing the terminological and phraseological consistencies of larger and ongoing localization projects, thus contributing greatly to the overall quality of the product. These databases, however, first have to be filled with highly reliable data, i.e. terms or larger segments, translation elements whose quality can be optimized by the right combination of translator tools and translator skills. Those skills and tools are also very important with regard to continuously ensuring the quality of TM and term base contents. With regard to preparing translation students for the professional realities of technical translation and localization, we recommend specialized curricular modules based on the localization tool, text, and process typology presented in this article. 19

20 5 References Akis, Jennifer Wells and William R. Sisson (2002): "Improving Translatability: A Case Study at Sun Microsystems, Inc. " LISA Newsletter: Globalisation Insider, Volume XI, Number 4.5. [ Albrecht, Jörn, Frank Austermühl and Joachim Kornelius (eds.) (1999): etb - electronic term books. Trier: WVT Wissenschaftlicher Verlag Trier. Vol. 1. Umwelt. Austermühl, Frank (2001a): Übersetzen im Informationszeitalter - Überlegungen zur Zukunft fachkommunikativen und interkulturellen Handelns im Global Village, Trier: WVT Wissenschaftlicher Verlag Trier. Austermühl, Frank (2001b): Electronic Tools for Translators. Manchester: St. Jerome. Austermühl, Frank and Joachim Kornelius (forthcoming): "Sprachdatenbanken für Übersetzer." Armin P. Frank et al. (eds.): Übersetzung - Translation - Traduction. Ein internationales Handbuch zur Übersetzungsforschung. Berlin, New York: De Gruyter. Briggs, Brian (2002): "The Importance of TMX for Translation Tool Buyers." Language Partners International, Inc. [ Bugel-Shunra, Dena (2002):. "Translation Project Management. T-Remote Memory." Multilingual Computing & Technology, Volume 13, Issue 6, September/October [ Enríquez Raído, Vanessa (2000): Aproximación a la situación actual del mercado de la «localización» en España: un análisis estadístico. Madrid: Universidad Alfonso X El Sabio. [http// Esselink, Bert (2000): A Practical Guide to Localization, Amsterdam, Philadelphia: John Benjamins. Fry, Deborah (2001): The Localization Industry Primer. LISA. [ Holderbaum, Anja and Joachim Kornelius (1999): "Über die Erschließung von Wissensbeständen der übersetzungsbezogenen Terminologiearbeit und ihre Dokumentation im Umfeld des electronic publishing". AREAS Hönig, Hans G. (1998): "Textverstehen und Recherchieren." Mary Snell-Hornby et al. (eds.): Handbuch Translation. Tübingen: Stauffenburg Hunt, Timothy (2002): "Translation Technology Failures and Future." LISA Newsletter XI, 4.6. [ 20

21 Hutchins, John and Harold Somers (1992): An Introduction to Machine Translation. London: Academic Press Ltd. Hutchins, John and Walter Hartmann (2002): Compendium of Translation Software. Version 1.4. [ Kornelius, Joachim (1995): "Vom Printwörterbuch zum elektronischen Kollokationswörterbuch. Theoretische, methodische und praktische Überlegungen zur Erstellung eines Kollokationswörterbuchs." Lexicographica 11, Macklovitch, Elliot and Graham Russell (2000): "What's Been Forgotten in Translation Memory?" John S. White (ed.): Envisioning Machine Translation in the Information Future: Proceedings of the 4th Conference of the Association for Machine translation in the Americas (AMTA 2000). Berlin, New York: Springer Melby, Alan K. (1992): 'The translator workstation', in: John Newton (ed.) Computers in Translation. London: Routledge, Melby, Alan K. (1995): The Possibilty of Language. Amsterdam, Philadelphia: John Benjamins. Melby, Alan K. (1998): Eight Types of Translation Technology. [ Nord, Christiane (1997): Translating as a Purposeful Activity. Functionalist Approaches Explained. Manchester: St. Jerome. Snell-Hornby, Mary, Hans G. Hönig, Paul Kussmaul and Peter A. Schmitt (eds.) (1998): Handbuch Translation. Tübingen: Stauffenburg. Sprung, Robert C. (ed.) (2000): Translating Into Success. Cutting-edge strategies for going multilingual in a global age. Amsterdam, Philadelphia: John Benjamins. Stolze, Radegundis (1992): Hermeneutisches Übersetzen. Linguistische Kategorien des Verstehens und Formulierens beim Übersetzen. Tübingen: Narr. Wilss, W. (1988): Kognition und Übersetzen. Zu Theorie und Praxis der menschlichen und maschinellen Übersetzung. Tübingen: Max Niemeyer Verlag. 21