Introducing linguistic transformation to improve translation memory retrieval. Results of a professional translators' survey for Spanish, French and Arabic

Translation memory systems (TMS) are the main component of computer-assisted translation (CAT) tools. They store translations allowing to save time by presenting translations on the database through matching of several types such as fuzzy matches, which are calculated by algorithms like the edit distance. However, studies have demonstrated the linguistic deficiencies of these systems and the difficulties in data retrieval or obtaining a high percentage of matching, especially after the application of syntactic and semantic transformations as the active/passive voice change, change of word order, substitution by a synonym or a personal pronoun, for instance. This paper presents the results of a pilot study where we analyze the qualitative and quantitative data of questionnaires conducted with professional translators of Spanish, French and Arabic in order to improve the effectiveness of TMS and explore all possibilities to integrate further linguistic processing from ten transformation types. The results are encouraging, and they allowed us to find out about the translation process itself; from which we propose a pre-editing processing tool to improve the matching and retrieving processes.