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Custom translation memory for consistency, efficiency and savings
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Custom translation memory for consistency, efficiency and savings

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This infographic shows how to use translation memory to drive down costs, decrease turn-around time & improve consistency.

This infographic shows how to use translation memory to drive down costs, decrease turn-around time & improve consistency.

Published in: Marketing, Technology, Business
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  • 1. How to drive down costs, decrease turn-around time & improve consistency with Translation Memory Keep Your Translation Memories Separate TMs are as unique as the content used to build them and isolating content improves consistency and decreases costs by limiting variances. In other words, it’s a good idea to keep separate legal and marketing TMs. For example, “Definitions are provided for guidance only” can be found in legal and other types of content, but for technical content it might be referring to something else, like software. By combining your TMs you run the risk of decreasing the efficiency of your TM and convoluting your ICE match rates. What is Translation Memory (TM)? TM is a database that stores segments of translated text in order to aid human translators, so the same sentence never needs to be translated, or paid for, twice. How it works. When you submit a file for translation, preferably in an editable format like a Word Document, the content is put into the TM. Then, the content is evaluated in segments against the database of previously translated terms and phrases. When the TM finds a match, it shares it with the human translator working on the text. They can accept or overwrite the suggestion depending on how it fits with the context of the current document. As your TM grows so does the likelihood of more matches, resulting in faster and more consistent translations at a lower cost. 2. Exact Match (AKA “100% matches”) This occurs when the same sentence has been translated before and the TM is able to find a word-for-word and in-sequence match in both the source document and the database, but the surrounding content may be different. “Definitions are provided for guidance only. Definitions used in the agreement shall have the same meaning under this addendum, unless expressly stated otherwise. These definitions do not apply at anytime outside of the European Union." Exact Match Example: “The Definitions provided are considered agreed and understood by all parties. Definitions used in the agreement shall have the same meaning under this addendum, unless expressly stated otherwise. These definitions do not apply at anytime outside of the European Union." Source Exact Match 1. In Context Exact Match (ICE) This is ultimately what your aiming for. An ICE match is an exact match that occurs in exactly the same context. In other words, the sentences surrounding the analyzed segment, as well as the segment itself, are exactly the same. ICE Match Example: “Definitions are provided for guidance only. Definitions used in the agreement shall have the same meaning under this addendum, unless expressly stated otherwise. These definitions do not apply at anytime outside of the European Union." Source ICE Match “Definitions are provided for guidance only. Definitions used in the agreement shall have the same meaning under this addendum, unless expressly stated otherwise. These definitions do not apply at anytime outside of the European Union." Definitions used within the agreement shall have the same meaning under the addendum, unless expressly stated otherwise. “Definitions are provided for guidance only. Definitions used in the agreement shall have the same meaning under this addendum, unless expressly stated otherwise. These definitions do not apply at anytime outside of the European Union." Source High Fuzzy Match Low Fuzzy Match Definitions used within the agreement will have the exact same meaning under within the addendum, unless expressly stated otherwise. 3. Fuzzy match When the segment match is not exact, it is a "fuzzy" match. Usually, percentages are assigned to these kinds of matches. For example, a fuzzy match can range from low (0%) to high (100%). Fuzzy Match Example: Copyright © 2014, All rights reserved. About VIA VIA provides accurate translation with a 99% on-time delivery rate. With a global network of over 5,000 translators with expertise in more than 125 languages, VIA uses its experience and scalability to seamlessly partner with large multinational corporations, including Cisco, HP, Walmart, Expedia, Nike, St. Jude Medical and more. For more information, visit us at www.viadelivers.com. Not all matches are created equal: TM will make suggestions on three types of matches The more consistent you are with your messaging in your source documents, the more likely you are to get ICE matches. Adopting glossaries and style guides can help you achieve the best match-rates possible for best-cost scenario. If the fuzzy match does not impact the context of the document then it can be less expensive to just use it. However, if it happens to change the meaning, such as in a legal contract, the translator may want to change it to be more accurate.

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