Abstract
The aim of the present article is to contend the widespread but largely unfounded claim that MAHT tools (popularly known as translator ’s work-benches) are best suited for translating so-called technical texts. The article calls for establishing a separate MAHT tool-specific text typology by pre-senting what are – in the author ’s opinion – the most important features characteristic of an MAHT-suitable text. It transpires that it is difficult to simply relate this particular type of text to any of the existing classifications of translation-related or general text typologies (such as those advocated by, for example, Hatim & Mason 1990; Reiß 1983; Snell-Hornby 1988 or Kussmaul 1997) since the existing methodologies do not take MAHT-specif¬ic attributes into account. Therefore, the present article calls for an empi¬rical, corpus-based study that would help establish the relation between the proposed underlying features and actual text types as described elsewhere.
Highlights
Before embarking on a discussion concerning the proposed outline of an MAHT-text typology it seems appropriate to define what is meant by Machine Assisted Human Translation
From the above discussion it transpires that the existing function or contentbased translation-oriented text typologies are insufficient to fully account for the novel text type that has become the focus of MAHT studies, i.e. an MAHT-suitable text, as I propose to call it
An analysis of MAHT-suitability leads to the creation of a new text typology. This is, not to say that traditional approaches to typology should not play any role in determining the characteristics of such texts
Summary
Before embarking on a discussion concerning the proposed outline of an MAHT-text typology it seems appropriate to define what is meant by Machine Assisted (or Aided) Human Translation. The human translator prepares the target language version of the text in question, and the machine (i.e. Marcin Feder a computer program) assists him in this task by, basically, offering terminological hints (i.e. terms are retrieved automatically, semi-automatically or manually from an appropriate database) and by building and employing a translation database (a Translation Memory - TM) to suggest identical (exact matches) and similar segments (fuzzy matches) that have been used in translations and stored in the database previously. Marcin Feder a computer program) assists him in this task by, basically, offering terminological hints (i.e. terms are retrieved automatically, semi-automatically or manually from an appropriate database) and by building and employing a translation database (a Translation Memory - TM) to suggest identical (exact matches) and similar segments (fuzzy matches) that have been used in translations and stored in the database previously It is this second instance of CAT that is the subject of the present article
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