Despite the exciting work accomplished over the past decade in the field of Statistical Machine Translation (SMT), we are still far from the point of being able to say that machine translation fully meets the needs of real-life users. In a previous study [6], we have shown how a SMT engine could benefit from terminological resources, especially when translating texts very different from those u...

This paper presents example-based machine translation architecture using translation memory that integrates the use of examples for flexible, idiomatic translations with the use of linguistic rules for broad coverage and grammatical accuracy. In examplebased machine translation (EBMT) approach to machine translation is often characterized by its use of a bilingual corpus with parallel texts as ...

Alongside increasing use of Machine Translation (MT) in translator workflows, Translation Memory (TM) continues to be a valuable tool providing complementary functionality, and is a technology that has evolved in recent years, in particular with developments around subsegment recall that attempt to leverage more content from TM data than segment-level fuzzy matching. But how fit-for-purpose is ...

Translation memory (TM) today widely used Computer-Assisted Translation (CAT) tool, based on matching of source and target language segments is intended for future reuse of already translated domain restricted type of texts. It is consistent, fast and cost-saving but the biggest lacks are non-existence of language knowledge and context insensitivity. Often integrated with machine translation (M...

Current Translation Memory (TM) systems work at the surface level and lack semantic knowledge while matching. This paper presents an approach to incorporating semantic knowledge in the form of paraphrasing in matching and retrieval. Most of the TMs use Levenshtein editdistance or some variation of it. Generating additional segments based on the paraphrases available in a segment results in expo...

In this paper, we present an algorithm for the automatic extraction of translation patterns between two (Indo-)European languages. These consist of possibly discontiguous text fragments, with the bilingual relationship between the text fragments and the discontinuities between them made explicit. The patterns are extracted from a bilingual parallel corpus aligned at the sentence level, without ...

Commercial off-the-shelf machine translation engines and translation support tools, such as translation memory (TM), have been developed primarily for translating grammatically well-formed, edited text. The real-world, foreign language (FL) document collections that our translators work with consist instead of noisy and complex image files. We are currently conducting experiments that involve b...

The term advanced leveraging refers to extensions beyond the current usage of translation memory (TM) in computer-aided translation (CAT). One of these extensions is the ability to identify and use matches on the sub-segment level — for instance, using sub-sentential elements when segments are sentences— to help the translator when a reasonable fuzzy-matched proposal is not available; some such...

Although undeniably useful for the translation of certain types of repetitive document, current translation memory technology is limited by the rudimentary techniques employed for approximate matching. Such systems, moreover, incorporate no real notion of a document, since the databases that underlie them are essentially composed of isolated sentence strings. As a result, current TM products ca...