Issue 1 – 2009 - Language Technology Division
Contents
1. Here will explain how the conversion process is done with Excel files because this is the most common file format for conversion and many other formats such as Word tables and csv files can easily be converted to Excel format You can find additional information regarding the other file formats in the MultiTerm User Guide or Online Help Converting Excel Data Step 1 Convert data l Prepare your glossary file in Excel so that each column has a header on the first row and the source and target term fields include only terms phrases and no explanations synonyms alternative endings or other information All the other information can be placed in separate columns which should then be labeled accordingly All the data has to be on the first worksheet of the file and there should be no empty columns between the columns that contain the data For example see Figure 1 2 Open Multilerm Convert Start gt All Programs gt SDL International gt SDL Multiferm 2007 gt SDL Multiferm 2007 Convert pear shaped body large hairy social bee E kina 9 Bumblebee kimalainen 0 Figure I A properly structured sample glossary in Excel format This glossary includes 8 terms rows 2 9 and 5 fields The field names are on the first row This screen allows you to specify the type of each column header field contained in the input file You need to specify the language for index fields Figure 2 Defining Index fields or Descriptive2. authors who use a controlled language have fewer choices available when writing a text For example the sentence Check the spelling of a paper before pub lishing it is a perfectly acceptable sentence in general English Using CLOUT a controlled language rule set developed by the author of this article the sample sentence would have to be rewritten as You must check the spelling of your document before you publish that docu ment to comply with rules regarding vocabulary active voice use of articles and avoidance of pronouns Why do we need controlled languages Facilitating language learning Probably the first controlled language Basic English was created by C K Ogden in 1930 The devel Oper had the explicit goal of dramatically reducing the 5 years it takes to master Standard English Based on a vocabulary that contains 850 essential words the Oxford English Dictionary on the other hand defines more than 600 000 words Basic English is designed to be acquired in just a few weeks Eliminating translation One of the most widely used controlled languages today is ASD STE100 Simplified Technical English also known as Simplified English Simplified English was originally developed by the European Association of Aerospace Manufacturers AECMA in the 1980s The main purpose of Simplified English was to create a variant of Standard English that aircraft engineers with only a limited command of Engl
3. button and then typing the first selection in the box Repeat this until all the picklist items have been added and click OK When you are satisfied with your descriptive field selections click Next 9 On the Entry Structure page review the entry struc ture of your termbase Again this should be correct because it is based on the definition you created during the conversion session Here you can also define each individual descriptive field as Mandatory the field has to appear at that level at least once in every entry or Multiple the selected field can appear several times at that level in every entry under the Field settings if needed When finished click Next When the Wizard Complete page comes up click Finish You now have a new empty termbase that is open in MultiTerm Next you need to import terms your converted data into the termbase See Step 3 mport terms Step 3 Import terms 1 In Multiferm select Termbase gt Import Entries This opens the Import tab in the Termbase Catalogue page Click Process not OK 2 Click Browse to select the XML file termbase data file you created in the conversion session Step 1 The Log file information is automatically filled out 3 Select the Fast import option and click Next 4 Click Next on the Import Definition Summary page and check how many entries were processed Click Next gt Finish That will take you back to the Import tab of the Termbase Cat
4. occur we must not be caught unprepared During 2004 concern about the treat of a pandemi preparedness activities coordinated by WHO that are leaving the world better prepared for the next pandemic whenever it occurs and whichever virus causes it world remains whether the present situation will tum out to be another narrow nates the need for exponentially duplicating bilingual memories En nous donnant un avertissement clair le virus H6N1 nous a laiss le temps de meux nous pr parer En 2004 le corante dune pand mie a domn leu une s rie d op rations coordonn es par OMS gr ce ast maintenant mieux prapar 4 la prochaine pand mie quels que soient le moment auquel alle reste cependart extr mement vuln rable Mul ne peut dire zi ta situation actuels montrera r trospectivement qu on I s chapp belle une foes de e plus ou ventualit curviendra et le vrus qui la causera De par sa grande mobit et ses nombreusas cera le pr tude la BZ U x a epe Repicom skp This philosophical difference means that on top of being able to preserve the context the lextBase TM technology enables you to rapidly build massive memories of legacy translations There is no need for costly manual verification of alignments before they can be used productively As a result you can create a much larger translation memory parallel corpus in a much shorter timeframe On most systems the TextBase TM can be create
5. 25 years has focused on providing the most efficient multi lingual information services and solutions STAR has developed the complete suite of technologies to fulfill that mission and makes all of its technology available to the open un sp cialiste marketplace Figure 7 next page For more information please visit www star group net O em Motches amp Terms View t Edt Processing Review Coury AFTAR sae 3s ata Create Open Delte Open Import Expert Insert Exec Send Forward Receive fy dete td Save As Sandnd i Tengate Temsta Pioect Dictionanes gt HTML Markup DEU HTML Markup E glish line of nan Transit TermStar and WebTerm are there to eat you thanks to their open architecture and ease of access They are STAR s Professional Translation Tools Most easy to use Each tool comes with a great wizard Html Viewer HIML Markup German Information 2005 sal April 2005 Wherever langua present themselves in your particular line of viia Transit TermStar and WebTerm are there to help you thanks to their open architecture and ease of access They are STAR s Professional Translation Tools Most easy to use Each tool comes with a great wizard lSGnsistent terminology is a prerequisite of high quality product information As you translate with Transit the source text is continuously searched for terminology stored in the database 1 Any terminology found is 1st colour highlighted in the text and 2nd disp
6. Organizations that wish to reduce the cost and time involved in the translation of their materials is the fact that even in environments that combine content management systems with translation memory technology the percentage of untranslated segments per new project can remain fairly high While it is certainly possible to manage content on the sentence segment level the current best practice seems to be to chunk at the topic level Chunking at the topic level means that reuse occurs at a fairly high level of granularity In other words There is too much variability within these topics Controlled authoring for translation memory systems Writing in a controlled language reduces variability especially if the controlled language not only covers grammar style and vocabulary but also function In a functional approach to controlled language authoring there are specific rules for text functions such as instructions results or a warning message Here are two simple examples for functional controlled language rules Text function Instructions Pattern Verb infinitive article object punctuation mark Example Click the button Text function Results Pattern Article object verb present tense punctuation mark Example The window Expense Report appears Implementing functional controlled language rules will enable authors to write text where sentences with the same function have a very high degree of si
7. There you can look at a given problem through the eyes of a Mac user in Japan a Linux user in Germany and a Windows PC user in Russia It is a trader s bazaar of knowledge experience and suggestions from all over the world Staffed entirely by volunteers The first step in Omegal is to create a pro ject Set up your source and target languages and accept the default folders Later when you Thelma L Sabim a native of Brazil has been working as a full time freelance translator in Austin Texas and Curitiba Parana since 1989 She is a certified translator in the USA and Brazil and a volunteer localizer of this open source CAT tool She can be contacted at tlsabim portuguesetranslator net get more familiar with the program you can fiddle with these settings See Fig 1 The source files need to be placed in the source folder Microsoft Office files must be converted into OpenOffice formats first See Fig 2 Any translation memory in tmx tormat will go into the TM folder The number of TMs is limited by the power of your PC Technically you can use as many TMs as you or your PC want The option of including multiple f e types and pre existing memories within a project helps ensure consistency can see how translated a phrase on a Slide and with a single click can see how the same sentence came out in the manual Fig 3 shows the segment 0055 Fuzzy matching opened for translation and the matches
8. a controlled language Improved usability Documents that are more readable and more comprehensible improve the usability of a product or service and reduce the number of Support calls Objective metrics and author support Tools driven controlled language environ ments enable the automation of many editing tasks and provide objective quality metrics for the authoring process Controlled language environments also provide authors with powerful tools that give them objective and Structured support in a typically rather Subjective and unstructured environment Lower translation costs As controlled language texts are more uniform and standardized than uncontrolled ones controlled language source documents typically have higher match rates when processed in a translation memory system than uncontrolled source documents Higher match rates mean lower translation costs and higher translation speed Some controlled languages have been specifically designed with machine translation in mind e g Caterpillar Technical English or this authors Controlled Language Optimized for Uniform Translation CLOUT Using a controlled language customized for a specific machine translation system will significantly improve the quality of machine generated translation proposals and dramatically reduce the time and cost associated with human translators editing those proposals Impact on translation Status quo One of the biggest challenges facing
9. bilingual corpus which they call by different names and a terminology database using the same Interface You can search all files or just a subset of them They also all provide automatic alignment tools which are preferable to the manual alignment required by most translation environment tools which assume you will populate the TM while translating in the tool s environment rather than by importing translations done outside it They are extremely useful where translation environment tools usually fall short when the text to be translated is in a format that cannot be imported Examples are paper documents and scanned pdfs asked four corpus tool vendors to answer the following questions e How does working with a corpus based tool differ from working with a TM based tool e What are the advantages e How does your tool use corpora Their answers are printed below The main features of each tool are FIND by Beetext e Find is not an environment tool but it can work as part of a software suite that includes a translation environment tool called Echo e Find searches for terms in a terminology database and in your bitexts from the same interface displaying all results on one page 1 Note that the plural of corpus is corpora Logiferm by Terminotix e Logilerm is not an environment tool but it does per form preprocessing on text files inserting bitext and terminology matches into a copy of the source file It cal
10. is an English to Finnish translator and Trados trainer and has given several Trados workshops and presentations For more Trados help information see www finntranslations com tradoshelp Register for the Mailing List lf you haven t already done so be sure to subscribe to the LID mailing list Go to the Division s website http www ata divisions org LID and click on 12 LID Mailinglist Our listmaster Katrin Rippel can t wait to hear from you Corpus tools for translators allow bilingual corpus and same interface Product Survey Naomi Sutcliffe de Moraes A Survey of Corpus Tools for Translators in the Words of the Vendors Themselves Let me begin by defining some terms When most people think of translation tools they think of a translation environment tool using a Translation Memory TM e A translation environment tool is a tool which imports your source file in some way then leads you sentence by sentence through it providing a field or cell in which to type the translation then exports the target file in some way so that the layout of the finished translation mimics that of you to search a parallel aligned a terminology the original Each tool performs these steps database using the differently e Translation Memory commonly called TM is a database of sentences from prior translations linked with their translations Tools working with TMs can
11. or sentence group is perfectly aligned and because the documents are split into individual sentences the context is lost The Multilrans TextBase IM parallel corpora indexes your integral documents in a side by side manner Since the technology does not divide documents into individual sentences Multilrans can easily align paragraphs and sentences at a near perfect level with out any human intervention Furthermore the context of your past translations the entire document is pre served This means that in the rare cases of misalign iamolig Window Help Term ane bird flu temno v Langusge Engish Maste i se FZ ADS CUL Target French OMS Grippe aviaire questions jiLes oiseaux migrateurs propagent ils les virus hautement pathogenes 7 Quelles caract ristiques sp ciales pr sentent les flamb es actuelles chez les volailles Quels sont les pays qui ont t touch s par des hat ls avian influenza hich viruses Cause highly pathogenic disease hatis special about the current outbreaks in poultry hich countries have been affected by outbreaks in iambees chez les voizilles A classical translation memory poultry What are the implications for human health Where have human cases occurred How do people become infected Does the virus spread easily frorn birds to humans What about the pandemic risk What changes are needed for HSN to become a pandemic virus hat is the significance of li
12. 6 shows Transit NAl s capability to align and retrieve reference material in context This capability is only possible because segments are stored in context as a multilingual file based TM as opposed to being stored as isolated segments in a database While the above example shows typical pre translation capability in Transit NXT the following con text sensitive functions are also available in Transit NA in order to accelerate and improve the translator s productivity e Terminology Management TermStarN Transit NXT S terminology component assures the correct term is always used e Concordance Search quickly searches the current project files as well as reference material for indi vidual words phrases or similar terms to see the context in which they are used e Dynamic Linking similar to concordance search Dynamic Linking searches both a source and target language for translated pairs of individual words phrases or similar terms to see the context in which they are used e Dual Fuzzy if no matches are found in the source text Transit NAT searches the target text for similar sentences while the translation is being entered Transit NXT also searches both the source and the target language reference materials for suggestions e Sync View provides additional context by displaying the document and software layout as well as corres ponding graphics in the Sync View window STAR is an industry leader that for
13. LANGUAGE TECH NEWS G G A Publication of the Language Technology Division of the American Translators Association gim ie From the Assistant Administrator Once again we have a variety of articles for your reading pleasure not just on translation tools but on broader subjects as well Due to the way ATA divisions work most of a division administrator s activities are focused on the annual conference Some language divisions have a mid year conference but the tools seminar held this year in San Francisco in March was organized by the AIA Professional Development Committee not by the LID Indeed many tasks that would perhaps normally fall to the LTD such as evaluation of proposed talks for the annual conference are actually performed by the ATA Translation and Computers Committee which predates the LID I am also on the Committee for full disclosure One thing the LID does is to find distinguished speakers for the annual conference who then have to be approved by the conference organizer in order to be reimbursed for travel and hotel expenses have been working hard and have found two outstanding speakers Dr Lisa Sattler a specialist in physical therapy who will talk about office ergonomics and Prof Klaus Dirk Schmitz of the Cologne University of Applied Sciences who will talk about terminology See page 2 for details about their talks Note that the distinguished speakers have to be individuals who do not n
14. LTD Administrator Dierk Seeburg info icotext com LTD Assistant Administrator Naomi J Sutcliffe de Moraes www justrightcommunications com Call for Nominations The Language Technology Division is pleased to call for nominations from the LTD member ship for the following positions Administrator 2 yr term Assistant Administrator 2 yr term Election of these officers is held every two years in accordance with the LTD bylaws The results of the election will be announced at the LID Annual Meeting which will be held during ATA s 50th Annual Conference in New York City October 28 31 2009 LTD Officer Duties Officers must be members of the Language Technology Division as well as voting members of ATA You will find a summary of duties for both the administrator and assistant administrator positions online at http www americantranslators org divisions Officer_Duties pdt Serving in a division leadership role provides enormous opportunity both professionally and personally Division officers frequently find themselves becoming more successful in their own careers as they develop additional skills make useful business connections and share ideas with other division members How to Nominate a Candidate Your assistance in helping the LID Nominating Committee identify interested capable colleagues is crucial to the election process and the division Qualified candidates must be voting active or corres
15. The last column Type contains the field in which the term or expression was found e he Domain and Client Fields In these fields you can select the domain and the client related to the entry You can either choose from the drop down menu or type a new entry in the field Once you have entered a new entry it is added to the list for future reference eSynonym and Abbreviation Fields These fields contain e Notes and Definition Fields Enter the definition and a synonym and an abbreviation for the term and for its personal notes in these fields equivalent These fields are included in the search Figure 2 Lexocon Interface Beetext FIND the context The context field is filled automatically when an entry is created from a bitext and the original file name is displayed under the context field e Context Fields These fields contain a context for the For more information about FIND Desktop or Server term and its equivalent which are displayed in bold in edition please visit www beetext com 19 Logilerm Terminetix inc The term translation memory originally referred to a tool that LogTermWed Databases Termum Ps Grand Oxtionnsre Search results advisory committee Now Search TERMINOLOGY ENGLISH 2 fevtew comentioe 3 Canadian Transistion industry Sectoral Committee TrancSearch ONTEM Googe SO results 1 98 TERMINOLOGY FRANCAIS Domain s Comt consultatd sur f automobile c
16. alogue dialog box Click OK That s it The first imported entry should now be displayed in the entry pane of Multilerm see Figure 4 lf you want to use your Multilerm termbase with Trados see Using Trados lerm Recognition Feature in the previous Multilerm article January 2009 Exchanging Termbases with Others There are two different ways to exchange termbases either by creating and loading an MDB file or by using XDT termbase definition and XML termbase data files If you are using Multilerm 7 x it s easiest to exchange termbases as MDB files as follows Figure 4 Our converted sample glossary as it appears in Multilerm with the first term Ant displayed in the Entry pane and the other entries listed in the smaller Browse pane on the left Note the location of the three Descriptive fields in the open entry Giving a termbase mdb file to someone else Create an MDB file e Select Termbase gt Package Delete Termbase e Select the desired termbase from the list and name the new MDB file by selecting the Package the termbase to this file option clicking Browse and then selecting the target folder and entering the name for the MDB file in the File name box Click Save Make sure that the Delete termbase permanently option is not selected unless you really want to delete the termbase Click OK Answer Yes to the annoying Are you sure you want to do this question that pops up e Note that Multilerm does no
17. ape de subschant Si la Commission conch quune l gislation europ enne s impose ele labore une ofc mement Ele pubbe S quemment des ires verts ot Ges inves blancs de G amp sposer dune image aussi compl te que possible Figure 3 Bitext search results shown in context Logiterm is open and visible There is no black box as Is the case with most translation memories Context is Just a Click Away Bitexts are complete documents so when you search a Logilerm module the context of each result segment Is just a click away If you click on bitext result 1 Figure 3 that result is shown in the context of the original file from which it was taken This is possible because segments are aligned linearly and bitexts are always kept in individual files they are never combined as with translation memories Best Match Source Text Analysis Traditional translation memories are like collections of sentences while Logilerm modules are more like collections of documents The analysis performed by Logilrans automatically gives priority to the bitexts that are most similar overall to the source text and shows these results first because the translations in those bitexts will likely be more relevant Additionally the translations retrieved will be more consistent since they come from a smaller number of bitexts Furthermore you can set up Logilrans to use a Specific bitext as a data source just as you would a Logile
18. ate the glossary first in Excel and then import it into Multilerm The reason is that entering a large number of terms is faster in Excel than in Multilerm Converting Terminology Data to MultiTerm XML Format SDL Multilerm comes with a separate application called SDL Multilerm Convert which allows you to convert your non Multilerm glossaries into Multilerm termbases You can convert the following file formats Multilerm 5 format Olif XML format SDL Termbase Desktop format e SDL Termbase Online format e Spreadsheet or database exchange format e Microsoft Excel format The conversion is a three step process First you create an xml and xdt file from the source file using Multilerm Convert The XML file is the termbase data file that includes the actual terminology data while the XDI file is the termbase definition file that contains the Structure of the termbase The second step is to create a new termbase in Multilerm based on the XDI file and the third step is to import the data in the XML Tile into the new termbase This might sound a wee bit complicated and must admit that it is a more complicated process than it should be however if you know what to do it works quite quickly and smoothly Regardless of the format of the source file the last two steps of the process are always the same Only the first step conversion to XML and XDT files which is done in Multilerm Convert varies depending on the source Tile type
19. available in the TMs can type Ctrl 1 to highlight Option 1 or Ctrl 2 to highlight Option 2 Then Ctrl l inserts the selected match in the opened segment OmegaT works with pre existing glossaries too The file needs to be in three columns and in the tab delimited format do not have experience working with glossaries in Omegal but the User s Manual has detailed information about this feature When the translation is finished the next step is to save the project and then create the target file s It is a good idea to save the project and create the target file also during the translation process Fig 4 page 20 To view translated documents during translation just click on the files in the target folder Fig 2 The last step is to convert the two files back into Microsoft format if necessary One folder each for terminology source files translated files a Omegal 1 8 1_2 sample Project Edit Go To View Tools Options Help Edit Project Edit project properties here Source Files Language EN Translated Files Language PT BR z M Enable Sentence level Seqmenting Segmentation Source Files Directory Wae DAb sample sample sources i Translation Memory directory Browse b b sampleisamplestmn Glossary Directory Browse Db sampleisample glossary Translated Files Directory Browse D p sample sa mple target Figure 1 above source File Edit View Favor
20. d at the astonishing rate of 6 to 10 million words per hour This means that instead of being limited to the size of a conventional TM which often remains small because of the effort it takes to build you can now index all of your legacy documentation Having a larger pool of reliable previously translated data to compare against means that you will find a lot more repetition This increases quality terminology cohesion and productivity Since it is based on full texts the TextBase TM approach also enables enhanced data mining when com paring a document against the TM Since the TM is not segmented mining can take place on full paragraphs 8 STAR Transit NXT Its All About the Context While the whole idea behind corpora and translation memory TM is to increase translator con sistency and productivity a basic quality principle states that the quality of an output is relative to the quality of the input Therefore in transla tions the quality of proposals based on TM is directly related to the quality of the reference material the TM is built upon STAR In order to leverage existing translations multil ingual reference material can be created through align ment of source and target documents and files However when building translation reference materials con textually correct subject matter alignment is critical 18 Source Content Assesting_pandemic_thest_EN txt Options Context f i ritil Add T
21. d by these machine translation systems Is bound to improve dramatically Do have to develop my own controlled language Not at all Today many organizations that wish to reap the benefits of controlled language authoring opt for a software driven solution that comes with a built in set of grammar and style rules Systems like acrolinx IQ Suite Al CLAT or Tedopres HyperSTE have enabled literally thousands of organizations to improve the quality and productivity of their authoring and translation processes In a software driven authoring environment Organizations do not have to maintain the staff of highly trained linguistic experts needed to develop and deploy a proprietary controlled language Instead the organization simply selects the rules that are most suitable for a given content type from a set of preexisting writing rules Typically these checking tools Support the definition of multiple sets of rules for multiple types of content e g stricter rules for user documentation than for knowledge base articles Terminology management support From a technology standpoint it Is relatively easy to implement the rules part of a controlled language the terminology part Is typically more labor intensive It is certainly true that many controlled language software solutions include a module for collecting terminology However the task of creating a corporate dictionary which is what this job amounts to might be daunting N
22. el Standard English NSE Oc Controlled English Siemens Siemens DokumentationsDeutsch scania Scania Swedish Sun Microsystems Sun Controlled English Xerox Xerox Multilingual Customized English lation quality in rule based machine transla tion environments Enhancing comprehensibility Helping authors avoid both semantic and syn tactic ambiguity has been recognized as a goal worth pursuing in and by itself especially in the domain of technical communication Some organizations are deploying a controlled lan guage for the sole purpose of improving the user exper lence of a product or ser vice in the domestic market Common features One characteristic that most controlled languages share is the fact that very little information about their rule sets and vocabularies is freely avai lable This is not really surprising when you consider the fact that a controlled language holds the promise of giving the organization that uses it a distinct advantage over Its competition The other feature many controlled lan guages have in common is their dissimilarity Nortel Standard English for instance has only a little over a dozen rules while Caterpillar Technical English consists of more than ten times as many A recent comparative analysis of eight controlled English languages found that the number of shared features was exactly one i e a preference for short sentences Y Why should my organization use
23. er the Index field or Descriptive field radio button Let s Say you used English as the column header for your English term column Select English in the list of column headers then select the Index field radio button and select English trom the pull down menu Do this for all the other language fields in the glossary See Figure 2 Next specify the descriptive fields All descriptive fields are text fields by default If your descriptive fields are not text fields you can change their field type by first selecting the field in question in the Available column header fields list and then selecting the appropriate field type from the pull down menu under the Descriptive field button The available field types are Text Number Boolean Date Picklist and Multimedia file When you have specified all the fields click Next Create the entry structure by adding the descriptive fields to their correct locations within the Structure This is really your own decision and depends on your glossary structure If you are unsure where the fields should go just place them Somewhere in the structure You will see later how logical or illogical the locations were and can change them If needed The location of a field within the glossary structure does not affect how Multilerm works with Trados Workbench To add a field to a location select one of the descriptive fields under Available descriptive fields and then select the locati
24. erm Target Context Assessing_pandemec_theeat_tr txt J Figure 5 Translation Agent Full paragraph matches retaining the full document context Instead of assembling a paragraph to be translated from disparate sentences that do not flow together the TextBase TM will identify exact paragraph matches and then return the full paragraph as a single retrieved translation segment Like classic TM systems MultiTrans also identifies and replaces full and fuzzy sentences It is however designed to go beyond the segment to proactively identify sub segments This means that segments that fall below the fuzzy level which are ignored by most conventional IM systems are actually identified by Multilrans and this increases your multilingual asset pool tremendously In other words with Multilrans you can get a lot more repetitions more cohesiveness and greater productivity gains For more information about Multilrans visit www multicorpora ca Although Transit NXT is generally classified as a translation memory tool it embodies many of the char acteristics of a corpus tool While the classic alignment and IM tools focus on storing isolated segments the highest quality TM systems such as Transit NAT will prioritize contextually relevant suggestions because without context errors will occur There are two approaches to aligning and storing source and target segments One is to store them with context as Transit NX does the o
25. fields Each of the 5 fields has to be defined as an Index field or a Descriptive field Note that MultiTerm does not automatically define a field as an index language field even if the field name such as English is clearly a name of a language 3 Specify conversion session options New Save Existing Select New conversion session if you do not have a previous session that you would like to reuse You can save your new conversion session by selecting Save conversion session and giving a name and folder for the session file Note that this Is only the conversion session file and not the actual termbase In most cases there is no need to save the session If you want to reuse an existing session instead of creating a new one select Load existing conversion session After you have selected the options click Next 4 Specify the file type of the source file Since we are converting an Excel file select Microsoft Excel format Click Next D Specify the input file in the Input file box by clicking Browse and then locating the Excel file that you want to convert The other three file names will be filled out automatically and the files will be placed into the same folder where your input file is Click Next 10 10 specify which ones of the Available column header fields are index fields languages and which ones are descriptive fields Do this by selecting one of the listed header fields and then selecting eith
26. h eae FRE doesnt need alignment correction wiih N e The Create Entry button allows you mms reat rast j a a Find est tr s rapide to automatically create a new entry M very smie pine HME supports all popular documents format in the lexicon from the bitext Just rid appari isa Honest diein pepidaen i 7 GMM siso integrates a detailled lexicon and allows you to quickly create highlight an expression in both texts lexicon entries based on your bi text documents Find contient aussi un lexique d taill et permet la cr ation de fiches lexicales partir de votre bi texte en un clin d i and click on the Create Entry button The highlighted expression in the left side window will appear in the Term field of the new entry and the phrase on the right side will appear in the Equivalent field FIND will also automatically extract a context and place it in the Context menu Regetration Search Help field for each version Figure 1 A result matched to several documents in Beetext FIND A Integrated Lexicon Terminology Database Tert de l export FIND s lexicon is user friendly and fast Here is an overview of the lexicon interface and a description of its components Figure 2 Term The following features are shown in Lexicon mode Fave s Example dune fehe tenons Lo teme ost A gaxha etsan E e Result List The lexicon result list works like the bitext result list
27. hich to import the converted data See Step 2 Create a new termbase Step 2 Create a new termbase l Open Multiferm Start gt All Programs gt SDL International gt SDL Multiferm 2007 gt SDL Multiferm 2007 2 Select Termbase gt Create Termbase 3 Choose termbase location You might want to create one specific folder for all your Multilerm glossaries 4 The Termbase Wizard window comes up Run the Wizard by selecting Next 5 In the Termbase Definition window select Load an existing termbase definition file option and locate the XDT file termbase definition file that was created during the conversion session in Step 1 6 Click Next and enter a name for the termbase in the Termbase Name window under Name You can also add optional description and copyright information here If you click Add More you can even add a splash screen and icon for the termbase Click Next 7 On the Index Fields page verity the index fields information This should be correct because it is based on the definition you created during the con version session Click Next 8 On the Descriptive Fields page verify the descrip tive fields information This also should be correct 11 because it is based on the definition you created during the conversion session However note that if you defined any of the fields as picklist type you need to create the picklist of available choices in the Picklist box by clicking the New Insert
28. ing year if not as a candidate for office then perhaps as a contributor to our division newsletter or by giving a talk at the annual conference There are many ways to be involved and volunteering is a wonderful way not only to share your experience but also to expand your network of contacts As always your support of the Language Technology Division and ATA is appreciated Thank you 2009 LID Nominating Committee Controlled Language Does My Company Need It By Uwe Muegge ih q a TA HIO ak E Sill a sentence Structure Here is how they work and how your company can benefit from intro ducing a controlled language What is a controlled language Editor s Note This article has been reprinted with permission of tcworld magazine www tcworld info and it can be accessed at www tcworld info file tcworld_2009_02 pdf A controlled language is a subset of a natural language as opposed to an artificial or constructed language Natural languages such as English or German are languages that are used by humans for general com munication A controlled language differs from the general language in two significant ways 1 The grammar rules of a controlled lan guage are typically more restrictive than those of the general language 2 The vocabulary of a controlled language typically contains only a fraction of the number of words that are permissible in the general language As a result
29. ish could understand thereby eliminating the need to translate maintenance manuals into foreign languages Streamlining translation Within the localization industry many people familiar with the controlled language concept associate controlled language with automating the translation process In fact it typically comes as a surprise that controlled languages can and have been used for purposes other than making the translation process more efficient By restricting both vocabulary and style using a controlled language typically improves match rates in translation memory environments and trans Uwe Muegge is the Director of MedLION the life science division of CSOFT He is currently a member of TC37 at the International Organization for Standardization ISO and teaches graduate courses in Terminology Management and Computer Assisted Translation at the Monterey Institute of International Studies Uwe can be contacted at uwe muegge medl10n com Visit his website at www med 10n com Examples of organizations that have created a controlled language Alcatel Controlled English Grammar COGRAM Avaya Avaya Controlled English ACE Caterpillar Caterpillar Technical English CTE Caterpillar Fundamental English CFE Dassault Aerospace Fran ais Rationalis Ericsson Ericsson English General Motors GM Controlled Automotive Service Language CASL IBM Easy English Kodak International Service Language Nortel Nort
30. ites Tools Help Grek O O search Folders jb 2 ery Folders HITA CAT odp index html Elreadme bet review omegaT odt 2 b sample sample E a glossary am aa G omegat translation memory gt O source Microsoft Office files must be converted into OpenOffice files Glossary o My web E Personal Figure 2 above Figure 3 below Omegal s compatibility with different p atforms is a selling point to me because I m planning to move to Linux It means won t have to spend a lot of time learning new CAT programs that only run on one operating system Another compatibility plus is that OmegaT doesn t pick fights with memory hungry speech recognition programs like Dragon and ViaVoice OmegaT now comes with Java File formats lt f1 gt lt f2 gt lt bra gt Fuzzy matching lt segment 0055 gt Fuzzy matching lt end segment Match propagation cont page 20 Word PowerPoint Excel handled by conversion through OpenOffice org software lt f0 gt HTML XHTML XLIFF Okapi lt f0 gt lt f1 Microsoft Office 2007 XML lt f2 gt lt f4 gt DocBook Plain Text PO lt 4 gt lt fo gt lt hr6 gt lt f6 gt lt f7 gt JavaHelp Java Resource Bundles OpenDocument ODF OpenOffice StarOffice HTML Help Compiler HCC INI files lt t7 gt Simultaneous processing of multiple file projects Different file formats in the same project simultaneo
31. juries A person may receive one of many diagnoses including tendinitis and carpal tunnel syndrome These overuse injuries are prevented and corrected in the same way Good posture and ergonomics work together to aid prevention and correction This 90 minute lecture will discuss the signs and symptoms of more common injuries to help you recognize them before they become severe It will include information about what you can do to heal or prevent injuries including detailed ergonomic recommendations posture training and stretches Prof Klaus Dirk Schmitz Cologne University of Applied Sciences Terminology management for localization of software user interfaces Thursday October 29 2 00 3 30pm The localization of software products has to deal with different types of text such as installation manuals on line help files packaging and marketing material websites and the software user interface While the first text types are more or less typical technical texts the user interface with menus dialog boxes tool tips and error messages requires a dedicated approach for terminology manage ment This session will demonstrate terminological phenomena typical of software user interfaces discuss the value of traditional terminology manage ment for this kind of technical text and develop a proposal for an adequate terminological data model Learn from terminology standards How can freelance translators and small language service
32. layed with its translation in the dictionary window gt an m language barrier S S Sprachbarriere onary Die INX TINO TeemStarNat mid gt WOO Further Reading For further reading on the subject of corpus tools see the following two articles The Translators Binoculars ATA Chronicle Part 1 August 2008 Part 2 September 2008 For a full review of Logilerm see the following two articles Logilerm Your Personal Search Engine ATA Chronicle Part 1 November 2007 Part 2 January 2008 P ap Figure 7 Transit NXT s User Interface showing the translator s work environment including dynamic terminology control and end layout preview Sync View Found CAT cont from page 8 As a user and volunteer localizer of OmegaT had a front row seat during the group s successful inclusion of the OpenOffice org spellchecker and TMX format w Omegal 1 8 1_2 sample Project Edit GoTo View Tools Options Help apen c frase no slide ec Import Source Files Import From MediaWiki Reload iatatormas outro Close LUX em alguns mes Create Translated Documents Praperties Project Files Cait Figure 4 yaT nao briga co usam grande pa compatibility enhancement efforts not to mention improved support for right to left and non Latin alphabet languages As write one of the developers just finished a script to allow OmegaT to accept Trados generated ttx files To conve
33. ld be noted that scanned documents are an image of a text and thus FIND will not be able to extract text from them Automatic Bitext Display When a search ts Initiated results from the bitext search as well as the lexicon are automatically dis played Each section contains its own result list Search results are returned in a flash and the searched terms will be highlighted in the text shown by FIND Figure 1 next page is a screen capture of a result matched to several documents Each component is described below e The Previous and Next buttons at the bottom left of the screen will toggle from one occurrence to another in the selected document The corresponding document will scroll accordingly e The Previous and Next buttons at the bottom center will toggle from one document to another in the result list e The Previous and Next buttons at the bottom right of the screen will toggle from one corresponding version of the document to another For example if an English document is matched to a Spanish version a French 7 Beetext FIND version and a German version the right side buttons become active and allow you to switch from one version to another _ Brtext 5 E Lexicon 1 e he document names are dis 2 a a z a C Documents and Settings jfb Mes ffind en doc played as hyperlinks under the er TE E E E M texts This link will open the EAIA E e ONE OE apa E original document when clicked ee e
34. ls this feature Logilrans but it is part of Logilerm eLogilerm searches for terms in a terminology database in your bitexts and in reference texts from the same interface LogilermWeb displays all results on one page while the desktop version shows results in three different pages MultiTrans by MultiCorpora e Multilrans is both a translation environment tool that searches bitexts to find matches for segments to be translated and a stand alone corpus and terminology database search tool e Multilrans as a translation environment tool provides matching below the segment level at sub segment phrase level e Multilrans searches for terms in a terminology database and in your bitexts from the same interface displaying all results on different tabs Beetext FIND FIND Desktop is a search engine for translation pro fessionals to look up terms in their own translation archives bitexts featuring a visual bitext display function and a user friendly termi nology management interface The bitext function allows users to browse the source and target documents side by side and re use previously translated phrases sentences Or entire paragraphs in any translation environment such as a IM or a text editor The lexicon allows you to create terminological entries directly trom the bitext display or manually Lexicons can be exported in a CSV format from which they can be imported into a spread Sheet program such as Excel int
35. milarity This not only makes sentence modules reusable within and across topics in a content management system it also dramatically improves match rates in a translation memory system Controlled authoring for rules based machine translation systems Unlike in a traditional translation memory environment where uniformity is the decisive factor in improving efficiency the big factor for making machine translation systems more productive is reducing ambiguity in the source text The problem that rules based machine translation systems like Systran struggle with is the fact that in uncontrolled source texts the grammatical relationship between the words in a sentence is not always clear To enable rules based machine translation systems to generate better translations the controlled language needs to have rules like the following that helps the machine translation system successfully identity the part of speech of each word in a sentence Write sentences that have articles before nouns where possible Do not write Click button to launch program Write Click the button to launch the program Write sentences that repeat the noun instead of writing a pronoun Do not write The button expands into a window when you click it Write The button expands into a window when you click the button With rules in place that mitigate the weaknesses of rules based machine transla tion systems the quality of the output produce
36. mited human to human transmission How serious is the current pandemic risk re there any other causes for concern Why are pandemics such dreaded events What are the most important warning signals that a pandemic is about to start hat Is the status of vaccine development and Quelles sont les cons quences pour la sant de l homme THO at on observe des cas humains 1 Comment l homme esti infect iLe virus se propage t il facilement des oiseaux a fhomme Qu en esti du risque de pand mie Quelles modifications sant n cessaires pour que le virus H5N1 devienne un virus pand mique Quelle est la signification d une transmission interhumaine limit e 7 Queile est la grav du risque actuel de pand mie 7 Y atl d autres sujets de pr occupation Pourguol les pand mies inspirent elles une telle jingui tude Selected Text selected Text separates your document into out of 17 Source 25 Target 25 Deka 0 Figure 4 TextBase IM Full context at the entire document level ment you can easily realign a sen tence on the fly while you are translating Note that the Multilrans TextBase TM can be multilingual and multidirectional and therefore elimi Segment and Translation mobile and interconnected The HONI virus has given us not only a clear warning but time to enhance extremely vulnerable No one can say first pandemic of the 21st century Should the tatier even
37. o a translation memory or for sharing terminology with a colleague that uses FIND Desktop as well Beetext FIND is an affordable low maintenance tool that can be used with any document type repetitive or not It only takes a few minutes to get Started and start getting payoff from your investment gt beelext Project Efficiency Solutions Document Formats FIND recognizes most document formats such as WordPerfect Word PDF PowerPoint Excel html and more than 200 other formats In the case of PDF files it 14 e Multilrans parallel corpus may include more than two languages a tritext quadritext etc Transit NXT by STAR e Transit NXT is both a translation environment tool that searches bitexts to find matches for segments to be translated and a stand alone corpus and terminology database search tool e Transit NAT has a function in addition to the standard Source language concordance search that searches bitexts both source and target languages for trans lated pairs of words or phrases e Transit NXT automatically searches bitexts both source and target languages for matches e Transit Al s parallel corpus may include more than two languages a tritext quadritext etc Read the following descriptions provided by the vendors themselves and see what these corpus tools offer Where the vendors terms differ from those used above have added my standard terminology as a guide shou
38. omt examen TRA Stored source and target segments in a database a black box with little flexibility Nowadays trans lation memory tools are more flex ible especially in terms of displaying the context of a segment rapidly when pretranslating or searching however their architecture is still not as flexible as a product like Logilerm and its automatic retrieval tool Logilrans Let me explain why BITEXTS English To get the technical dotats rig t the Commission Consuls experts wa various sAssory commises and consult atre groups Document based Frequently publishes Green and White papers holds hearings seeks the views of chil society and commissions expert reports and oken consults the public directly before t makes a proposal in order to ensure that has as Complete a pecture as possibile Corpus based vs Segment based The document concept is central to Logilerm Aligning a pair of docu ments produces a bitext file which is a self contained HTML file that displays source and target texts side by side with segments aligned in the order in which they originally appeared linear alignment A bitext file can be saved to any disk location anyone can view it and perform searches without using Logilerm WYSIWYG File Management One advantage of using Logilerm is that a translator who stores client files in Windows folders can continue working in exactly the same way because bitext files are S
39. on in the Entry structure where the field should go and click Add Do this to all the descriptive fields You can also remove a field from the structure by selecting it and clicking Remove Note that a field can be inserted into more than one location in the entry structure When you are satisfied with the Structure click Next See Figure 3 The Conversion Summary window gives you a Summary of the files and their locations Check that Convert immediately is selected and click Next Check how many entries were successfully converted in the Converting window It should match the number of entries in your Excel file Click Next and then Finish 6 SDC Molhiterm Convert Select a field level in the entry structure and then select the descriptive field you want to add on the respective level in order to create your entry structure create Entry structure 09 Available desonptive fields Notes Entry structure Entry level ome en English S Tem Figure 3 Create a termbase entry structure by adding descriptive fields to their correct locations within the structure Here Notes field has been placed on the top Sample species under the English term and Esimerkkilaji Finnish sample species under the Finnish term For the resulting entry structure see Figure 4 The converted data XML file is now ready to be imported into a MultiTerm termbase However first you need to create a termbase into w
40. ons out of existing TMs bitexts e Preserve the full context of every segment even at the entire document level e Interactive translation module allows direct view of context ba Multilrans 4 TextBase Search TextBase Search Seach TexBases Terminology TextBases world heath organisation Source file Assessing p Assessing WHO Avian OMS Grippe WHO Lassaf OMS Flevre C A469 1 en ASS t fr A69__4 en A59_4 fr 459 10 4n 459 10 fr 459_11 en 459 _11 Fr 460_ 10 0n A60_ 10 fr AB0_1 en ABO tfr Pion Pt fr Target File file Edit Process View TextBase Search pa CO N b a Rw R m revised 5 December 2005 Do migratory birds spread the disease Data friendly Approach Aside from the best match capability mentioned above most of the strengths of Logilerm and Logilrans can be summed up in one expression data friendli ness Logilerm allows you to search in documents of many different types Data friendliness means less pre processing or conversion work for you and thus you can get the most out of your data in a wide range of Situations For more information visit www terminotix com about Logilerm context sentences and then tries to align them In layperson s terms It can be compared to an Excel work Sheet where for instance in one column you have the English and in another column the French equivalent sentences It is quite tedious to verify that each sentence
41. ormally attend AIA meetings and this usually means non ATA members and foreign linguists Last year s speaker was a monolingual computer repair technician Carey Holzman He gave many tips on how to deal with the Windows OS his specialty Outside of the annual conference our only VOL 3 NO 1 JULY 2009 Opportunities to talk to one another and share our knowledge are through the newsletter the mailing list IN THIS ISSUE and the blog on the LTD site Please visit the LTD site if you have not been there recently And if you are Interested in contributing to the blog or just want to Conference Speakers forward information for me or Michael Wahlster lt mwahlster gw language com gt to post on the blog Call for Nominations l please send one of us an email Controlled Language Does my Company Need It 0 4 This year is an election year for the LID so please Found CAT see the information on nominations on page 3 of this ont newsletter and please send in a nomination tocthe Trados Tip nominating committee We need you to participate A Survey of Corpus Tools for Translators Naomi Sutcliffe de Morges Assistant Administrator Distinguished Speakers 2009 Conference Dr Lisa Sattler The Importance of Ergonomics for Translators How to avoid repetitive strain injuries Friday October 30 2 00 3 30pm The injuries people get from sitting long hours at a computer are usually called repetitive strain in
42. ot only will all synonyms among the possibly thousands of terms in use at the organization have to be identified but these synonyms will also have to be categorized into preferred and depre cated do not use terms While creating a corporate dictionary may be a challenge once it is available that dictionary may also be the feature most valued by the users of the controlled language system Example of a controlled language To see an implementation of a simple controlled language designed for machine translation visit the author s website at www muegge cc The entire site was written in CLOUT the Controlled Language Optimized for Machine Translation On the home page click on any of the language combinations into English i e German gt English or French gt English and watch how Systran s free machine translation system turns a complete website into a fully navigable highly comprehensible virtual English site in real time Click on the link Controlled Language kules for Machine to see ten sample CLOUT writing rules that have a high impact on the comprehensibility and machine translatability of instructional text in English O Notes Ogden Charles Kay 1930 Basic English A General Introduction with Rules and Grammar London Treber 1930 ii Basic English Institute 1996 Ogden s Basic English Word List Ogden s Basic English Online 1996 Cited February 3 2009 http ogden basic english org wo
43. ponding mem bers of ATA and members of the Language Technology Division Any division member may make a nomination and self nominations are also welcome If you plan to put a name forward for a nomination it would be helpful if you could contact the potential nominee first and tell them of your intention Let them know that a nomi nation does not guarantee a formal invitation to run for office Remember that LID officers serve on a volunteer basis please do not nominate colleagues who express serious concerns about service or who have conflicting priorities To nominate a candidate for a LID office you may contact any member of the Nominating Committee listed below or download the Nomination Form from http www ata divisions org LID wpcontent uploads nom_form_ltd31mar09 doc The nomination form may be mailed or faxed to ATA Headquarters LTD Nominating Committee A Nominating Committee has been appointed to actively seek nominations for candidates Members of the 2009 ID Nominating Committee are Betty Welker Bettywelker cs com Jost Zetzsche jzetzsche internatinalwriters com Election Schedule July 24 Slate of candidates published Sept Deadline for receipt of petition to add candidates to slate Sept 18 Ballots mailed if more than one Candidate is running for any office Oct 23 Deadline for receipt of ballots We hope you will take this opportunity to consider stepping forward as a volunteer during the com
44. providers set up a detailed practical terminology management solution Saturday October 31 2 00 3 30pm International terminology standards such as ISO 16642 TMF ISO 12620 DatCats and ISO 30042 TBX as well as established best practices provide a set of principles and methods for setting up a terminology management system The language and translation departments of huge industrial companies and public organisations are not the only ones who can benefit from these guidelines Small language service providers and freelance translators should also make use of this professional know how This session will give a short theoretical background on terminology management explain basic design principles and typical data categories for termbases and show how terminology management systems can be used to support translators Language Tech News Vol 3 No 1 July 2009 Copyright 2009 American Translators Association 225 Reinekers Lane Suite 590 Alexandria VA 22314 Telephone 703 683 6100 Fax 703 683 6122 ata atanet org www atanet org Editor Roomy Naqvy roomynaqvy gmail com Editorial Committee Naomi J Sutcliffe de Moraes Barbara Guggemos Proofreader Naomi J Sutcliffe de Moraes Contributors to this Issue Tuomas Kostiainen Naomi J Sutcliffe de Moraes Uwe Muegge Thelma L Sabim Layout Cindy Gresham illustrator cgresham com LTD is the Language Technology Division of the American Translators Association
45. rds html iii AeroSpace and Defence Industries Association of Europe 2005 ASD STE100 Simplified Technical English International Specification for the Preparation of Maintenance Documentation in a Controlled Language ESSAS Electronic Supporting System for ASD Standardization Online 2005 Cited February 3 2009 http www asd stan org sales asdocs asp iv O Brien Sharon 2003 Controlling Controlled English An Analysis of Several Controlled Language Rule Sets Machine Translation Archive Online 2003 Cited February 3 2009 http www mt archive info CLT 2003 Obrien pdf Found CAT By Thelma L Sabim There are no fewer than twenty Computer Assisted http tech groups yahoo com group OmegaT Translation or CAT programs out there So how is one to choose As see it the three main factors are cost ease of use and compatibility Given the proliferation of new file types a program ought to be flexible enough to accom modate at least most of them without con Stantly bleeding your pocketbook for upgrades My favorite is Omega T It is open source avail able free of charge at http sourcetorge net projects omegat Since its official release in 2002 Omega T has attracted many devel opers and contributors no small fraction of whom are translators These are people living all over the world and running computers on different platforms Their sugges tions are posted on a Yahoo users list
46. rm module No preparation is required Translations in selected bitexts are given priority over translations in any selected modules Using Monolingual Reference Documents reference texts Another advantage of using Logilerm is that Logilrans can analyze the similarity of unilingual reference documents You can identity similarities to documents for which bitexts have not yet been created but for which translations are available Finally monolingual reference documents from clients or other sources can be searched manually in Logilerm and thereby provide valuable information Multifrans Working with a corpus based tool differs signifi cantly from working with TM based products In fact our technology alone is so different from classic TM systems that the Translation Automation User Society TAUS has coined our Technology Advanced Leveraging TM Some of the inherent advantages e Alignment benefits Provides context for each segment at paragraph level Produces quality 1 N and N 1 alignments rapidly Creates multi directional multilingual TMs bitexts or parallel aligned bilingual corpora Delivers ability to create a fully useable 10 000 segment IM parallel corpus in under five minutes e Advanced Leveraging Functionality Identifies and replaces match ing paragraphs Identifies sub segments and their translations in context within strings and sentences Provides more repetiti
47. rt other formats not directly supported Omegal also uses OpenOffice org Okapi Framework Windows only and the Translate ToolKit lf you are unsure about which CAT program to use would recommend that you try OmegaT It is free no strings attached Then if it seems like a poor fit you can ask questions and discuss issues on the Omegal list on Yahoo Omegal product improvement suggestions and new function requests should be sent to the Omegal project at sourceforge net To read more about Omegal please visit http en wikipedia org wiki Omegal or http www omegat org en omegat html O Call for Reviewers Are you using software that helps you in your day to day work as a translator and or interpreter Tell us about it Send reviews of your new favorite even most hated language technology software to Roomy Naqvy at roomynaqvy gmail com Your colleagues will thank you 20
48. store them however they wish often in proprietary formats or in the standard TMX format These databases usually do not contain much context information sometimes a code indicating the client the field or the translator The sentences are all mixed up in the database so later the translations may make no sense out of context Another less known tool for translators is a terminology database Most translation environment tools have one built in or one that is separate but compatible They allow you to input at least the source and target terms and sometimes much more information such as client field synonyms definition even images There is however a third kind of tool that incorpor ates facets of all three of the above types of translator tools the corpus tool What is a corpus you may ask A corpus is a collection of texts in electronic format They come in many flavors 4 E D A A oJ e Monolingual corpus aka reference texts many texts in a single language e Bilingual corpus many texts in two languages Parallel aligned bilingual corpus aka bitexts source texts and their translations aligned for com parison purposes The information stored is similar to that stored in a TM but the files are stored as a whole so when looking up a word or a sentence you have access to the entire document as context The corpus tools for translators described below allow you to search a parallel aligned
49. t give any confirmation or Indication that the process has succeeded The only way to find out is to check that the new MDB file was created in the folder you specified Give this MDB file to the person with whom you want to share the termbase Receiving a termbase mdb file from someone else If you receive an MDB Tile you need to load it in order to have the termbase available to you Load the file as follows e Select Termbase gt Load External Termbase e Locate the desired termbase MDB file by clicking Browse select the file and click Open The file name and path appear in the Termbase location box e Name the new termbase in the Termbase name text box and add a Termbase description if needed Click OK e Next you are offered an option to delete the MDB file after it has been loaded Answer Yes or No depending on whether you want to save it e You do not get any other indication about the process but the new termbase should be now available in your termbase list which you can access normally by selecting Termbase gt Open Close Termbases So now you should be able to create or load a termbase and use it with the automatic Term Recognition feature while translating with Trados In my next article will explain how to enter new terms directly from Word and TagEditor during translation and some other features that will make your Multilerm experience even more beautiful O Tuomas Kostiainen iuomas jps net
50. ther is to store them as Isolated segments The dominant industry alignment practice aligns segments in isolation in a database which leads to avoidable errors whereas aligned seg ments stored with context in a file system can still refer to the original document and its context The following example shows how segments in isola tion are stored and corresponding translations are pro posed Take note of the text highlighted in blue Now if the new source text below Is translated using English Source French Target Veillez a v rifier la mise a la terre Please check the existing grounding Si elle est d ficiente contacter un specialiste If it fails the test please refer to a professional reference segments stored in Isolation it would be translated as follows However in the new context of ground cable the New Source Please check the ground cable f it fails the test please refer to a professional Proposed Translation Veillez a v rifier la mise a la terre Si elle est deficiente contacter un specialiste translation of the second sentence should actually be Sil est deficient contacter un sp cialiste Using Transit NXT the correct translation would have been proposed because Transit NXT stores its TM with context and offers prioritized contextually relevant translation proposals Figure 6 English professional Document3 doc 19 Figure
51. tored by default in the same folder as the original files The following example shows files containing a source text bitext and target text Wacm Minutes e doc AGM Minutes e_ENG FRA_BT htm HI AGM Minutes F doc Modules are bitext groupings created in Logilerm that act similarly to a translation memory A module is actually a proxy pointing to folders that contain bitext Tiles Bitext files stay in their original locations and are always available The contents of a module can be determined by browsing its folders To change the con tents of any module you simply change the files in its folders or edit the contents of the bitext files Everything 16 gt a Senior project adveory commitiss SPAC on which ail stakeholders are represented the Comenismon concludes that EU legesiation is needed then drafts a proposal that it bebeves will deal with the problern ofiectnety and satisfy the widest possible range of interests v More recusts BITEXTS French v SUB MODULE Ele comsulte suss les experts qu forment ses e Oflorents consuttat s afin de s assurer que les OOMO r gi s Syma mese Sut ped dun comit consultati sup mew de projet CCSP au sem duquel tous les ettenenants sont orang repr sert s This approach of dealing with issues at the lowest possible levels Cette approche consistant 3 g rer les questions au pius bas called the subsidiarity principis meau possible s appede be pnn
52. us use of multiple TMs 1 Fuzzy matching Correspondencias imperteitas fuzzy matching lt 100 omegat web br tmx gt 2 Fuzzy matching Concordancia difusa lt 100 omegat web euro level1 tmx gt Trados Tip by Tuomas Kostiainen Using MultiTerm With Trados Part 2 Where Do Get MultiTerm Glossaries In my previous article January 2009 explained how Multilerm is used with Trados and how the Term Recognition feature works in Trados That s really good and important but if you don t know how to create or convert Multilerm glossaries it s all quite useless know that you all have been extremely anxious to get your hands on this follow up part so that you can put that great feature into practice So how do you get those Multilerm termbases You basically have the following three ways of getting them 1 By creating a new termbase from scratch 2 By converting an existing glossary from some other file format 3 By loading a Multilerm termbase in MDB format into your own termbase library In this article will concentrate on the Methods 2 and 3 because they are the most common and even if you want to create a glossary from scratch this is often easier to do using Method 2 If you want to create a new termbase and initially have only a small number of terms to add you can do it directly in MultiTerm However if you are planning to enter numerous terms into a new glossary you might want to cre
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