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  Tips — Writing for translations Applying the following methods will ease translation and help to avoid the misinterpretation that often results in translation errors. Avoid random or unnecessary capital letters.  Extra capital letters in English can fool the translator into assuming more words are brand names or proper nouns, changing how the text is translated. Even consider moving your corporate style toward upper case or “sentence case” for heads and subheads. Sentence case (first letter is capped) is very popular globally, while Americans often use “title caps” (select important words are capped) or all initial caps. EXAMPLES Upper case: THE RED BALL BOUNCES ONTO THE COURT. (preferred) Sentence case: The red ball bounces onto the court. (preferred) Title caps: The Red Ball Bounces onto the Court. Initial caps: The Red Ball Bounces Onto The Court.   Use short sentences, simple grammar, and “active voice” . Technical information resources will often include long, complicated se

A “Fuzzy Match” isn’t a fire hazard; it’s an indication of how well SDL Trados TM recognizes a text segment in a document. Translation Memory (TM) programs look for segments in memory that have enough content in common with the current document segment for the translation memory to be of use for translation. The match is expressed as a percentage. A complete match is called, not surprisingly, a 100% Match . Less than 100% is a Fuzzy Match . In general, 65-70% is considered the “fuzzy match threshold.” Depending on the settings chosen by the translation manager, the threshold can be as strict as 99%, or s flexible as 50%. Any matches that fall below the threshold are considered No Matches . For text segments that cannot be found in the TM, Trados marks the first instance as a No Match, and every other instance as a Repetition. This means a new translation can be entered once, then propagate to all instances of the segment. It is actually possible to have a match that is BETTER than 100

  What is Machine Translation? Machine Translation (MT) is the process by which computer software is used to translate text from one language to another (e.g. French into English). There are three general types of MT, each with their own set of strengths and weaknesses, covered in further detail at the end of this article ( [1] ) ( [2] ) . How Should MT Be Used? In the current state of the technology, machine translation still requires professional translators to work with the content to ensure that the translation is accurate to the source, idiomatic in the target language, and culturally appropriate for the target market. For non translators, MT serves best as a means to get a general idea of the message being conveyed, but should not be used for important professional communications, nor to produce content distributed outside the organization for the reasons outlined in the following section (1)(2)( [3] )( [4] )( [5] ) . Common Pitfalls of Using MT Without Translator Editing: Words

    About CPG Documentation LLC: CPG’s combination of full-service, in-house capabilities, and dedication to the highest level of customer service makes CPG the perfect partner. From technical writing and document translation to CAD conversions and desktop publishing: CPG can help. Location:  https://maps.google.com/?cid=6535135882796324461 YouTube:  https://youtu.be/PF33TAYYP5I G Site:  https://sites.google.com/view/cpg-technical-documentation/home/language-translation/localization-translation Twitter:  https://twitter.com/llc_cpg/status/1304137414710091783 CPG has been in the technical publication industry for the last 65 years. We deal with all kinds of document issues, and even the most discriminating customers are pleased. Give us a call to find out how we can help you. CPG takes pride in delivering a full range of services for businesses with unique needs and requirements. CPG has been in the technical publication industry for the last 65 years. We deal with all ki

  Translation Memory: Overview A translation memory (TM) is a bilingual database or software system that stores translated content and automatically suggests these stored translations when used with computer-assisted translation software (aka CAT tools). The entries in the database consists segments of text, such as words, sentences, and paragraphs [1] [2] . For example, consider the description below this famous painting by René Magritte: Photo credit:  http://museumtv.fr/portfolio/rene-magritte/ Note: This is not a pipe. It is a wonderful piece of art! If this phrase were to be translated into French for France, then the TM would look something like this: Later on in the same file or on a future project, the TM will provide translation suggestions if the source text is exactly the same or very similar. Very similar text is referred to as a “fuzzy match”, meaning that it is not an exact match, but it contains a certain percentage of the same text so that the previous translation could