Translation (EBMT)-do have something in common. Nevertheless, TM and MT technology-more precisely example-based machine Rather an information retrieval system of already translated texts done by humans. So, in contrast to a machine translation (MT) system which creates new translations not stored in the database, a TM is The presented TUs are useful for further processing. Retrieval mechanisms and are then presented to the user who can decide whether or not Whenever an identical or similar source language segment has to be translated, the corresponding TUs are retrieved from the TM by specific Storing a TU can either be done during the translation process or after finishing a translation and before starting a new one, respectively, a database, in which so-called translation units (TUs), consisting of source language segments and their target language counterparts mainly based In most of the cases, the TM of commercially available TMS is a Types of matches (Lagoudaki 2006 Reinke 2004).Īs for the components of a TMS, the translation memory (TM) constitutes theįundamental part. Using a TMS has different advantagesĭepending on the user’s perspective: from the translator’s point of view, the use ofĪ TMS increases productivity, translation quality and consistency, whereas the clientīenefits from lower translation costs by applying a specific pricing scheme for different (2006) gives evidence to this development.
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(CAT) and professional translation, respectively. In the last two decades of translation history, translation memory systems (TMS) haveīecome one of the most important tools in the field of computer aided translation Melanie Wei of Applied Linguistics, Translation and Interpreting, Saarland University, Identical repeating LCS and choosing the one with the minimal positional difference. If more than one identical repeating LCS between the sentencesĮxist, the best matching LCS is given by calculating positional differences for the In this way, identical repeating LCS within the same sentence are ignored, whereas identical repeating LCS between two different sentencesĪre still considered. Furthermore, an existing algorithm for generalized suffixĪrrays was enhanced by an additional array in order to distinguish which suffixesĭerive from which sentence.
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Base words were used forīuilding the suffixes to increase the probability of finding a larger number of LCSīetween both sentences.
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The so-called iMem-TM, an independent relational database which is connected to aĬommercial, non-linguistically enhanced TM via its API. The results of the morphosyntactic analysis are stored in Identifying the longest common substrings (LCS) between two sentences by means Retrieval of those very segments by analyzing their (morpho)syntactic structure and
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The iMem (iMem is an abbreviation for Intelligent Translation Memories) research project aimed at improving the Instead, linguistic similarities are disregarded so that semantically identical or similar segments, which have different (morpho)syntactic structures, are retrieved withĪ lower similarity value as expected or not at all. The commercially available systems still consider two segments to be compared similar if the sequence of characters is identical or differ only marginally in spelling. Most widely-used tools in the field of computer-aided translation. © Springer Science+Business Media Dordrecht 2017Ībstract Since the 1990s, translation memory (TM) systems have been one of the Improving retrieval performance of translation