This paper investigates the extent to which a useful general purpose Translation Memory (TM) can be built based on very large amounts of heterogeneous parallel texts mined from the Web. In particular, we evaluate whether such a TM could add value over TMs built from other large, publicly available parallel corpora, such as the Canadian Hansard. In the case of Canadian translators working with E...

Machine Translation (MT) quality is typically assessed using automatic evaluation metrics such as BLEU and TER. Despite being generally used in the industry for evaluating the usefulness of Translation Memory (TM) matches based on text similarity, fuzzy match values are not as widely used for this purpose in MT evaluation. We designed an experiment to test if this fuzzy score applied to MT outp...

This paper describes the new linguistic approaches of the MetaMorphoTM system, a linguistically enriched translation memory. Our aim was to develop an improved TM system that uses linguistic analysis in both source and destination languages to yield more exact matches to the source sentence. The MetaMorphoTM stores and retrieve subsentential segments and uses a linguistically based measure to d...

One key to the success of EBMT is the removal of the boundaries limiting the potential of translation memories. To bring EBMT to fruition, researchers and developers have to go beyond the self-imposed limitations of what is now traditional, in computing terms almost old fashioned, TM technology. Experiments have shown that the probability of finding exact matches at phrase level is higher than ...

In this paper, we extend an attention-based neural machine translation (NMT) model by allowing it to access an entire training set of parallel sentence pairs even after training. The proposed approach consists of two stages. In the first stage–retrieval stage–, an off-the-shelf, black-box search engine is used to retrieve a small subset of sentence pairs from a training set given a source sente...

Computer-assisted translation (CAT) tools have become the major language technology to support and facilitate the translation process. Those kind of programs store previously translated source texts and their equivalent target texts in a database and retrieve related segments during the translation of new texts. However, most of them are based on string or word edit distance, not allowing retri...

Transit (Translate it) ist ein professionelles Translation-Memory (TM) System entwickelt auf der Basis der langjährigen praktischen Erfahrung von STAR, eines der größten und erfolgreichsten Übersetzungsunternehmens der Welt. Die Kunden von STAR kommen aus der Automobilindustrie, der Informationstechnologie und dem Bereich Maschinenbau. Transit, das seit 1994 kommerziell als Produkt vertrieben w...

We present two methods that merge ideas from statistical machine translation (SMT) and translation memories (TM). We use a TM to retrieve matches for source segments, and replace the mismatched parts with instructions to an SMT system to fill in the gap. We show that for fuzzy matches of over 70%, one method outperforms both SMT and TM baselines.

this research aimed to review the use of second-person reference in advertisement translation, work out the general rules, and provide guidance to translators. using second-person reference is common in the advertising discourse. addressing audiences directly involves their attention and in this way enhances their memorization of the advertised message. second-person reference can be realized v...

The TELA structure, a set of layered and linked lattices, and the notion of Similarity between TELA structures, based on the Edit Distance, are introduced in order to formalize Translation Memories (TM). We show how this approach leads to a real gain in recall and precision, and allows extending TM towards rudimentary, yet useful Example-Based Machine Translation that we call Shallow Translation.