Abstract
Today technology is part and parcel of professional translation, and translation has therefore been characterised as Translator-Computer Interaction (TCI) (O’Brien 2012). Translation is increasingly carried out using Translation Memory (TM) systems which incorporate machine translation (MT), referred to as MT-assisted TM translation, and in this type of tool, translators switch between editing TM matches and post-editing MT matches. It is generally assumed that translators’ attitudes towards technology impact on this interaction with the technology. Drawing on Eagly/Chaiken’s (1995) definition of attitudes as evaluations of entities with favour or disfavour and on qualitative data from a workplace study of TCI, conducted as part of a PhD dissertation (Bundgaard 2017) and partly reported on in Bundgaard et al. (2016), this paper explores translator attitudes towards TCI in the form of MT-assisted TM translation. In doing so, the paper has a particular focus on the disfavour towards TCI expressed by translators. Moreover, inspired by Olohan (2011), who applies Pickering’s “mangle of practice” theory and analyses resistance and accommodation in TCI, the paper focuses on how translators accommodate resistances offered by the tool. The study shows that the translators express disfavour towards MT in many respects, but also acknowledge positive aspects of the technology and expect MT to play a significant role in their future working lives. The translators do not make many positive or negative comments about TM which might indicate that TM is a completely integrated part of their processes. The translators seem to have a flexible and pragmatic attitude towards TCI, adapting to the tool’s imperfections and accommodating its resistances.
Highlights
Today all professional translators interact with technology1, and drawing on the field of Human-Computer Interaction, O’Brien (2012) characterises translation as Translator-Computer Interaction (TCI)
Three types of Translation Memory (TM) matches are normally distinguished: If a new source segment is identical to a source segment stored in the TM, a 100% match will be retrieved; if the source segment is not identical, but similar to a segment in the TM, a fuzzy match will be retrieved; and if the TM contains no similar segment, we talk about a no match, in which case the translator will have to translate the new source segment from scratch
In systems which incorporate machine translation (MT) as an additional translation aid, the no matches are machine translated. This integration of TM and MT means that all segments for which the TM retrieves either a 100% or a fuzzy match are translated by means of matches stored in the TM, and the remaining segments are machine translated, resulting in a “hybrid” pretranslated text (Guerberof 2009: 1, Garcia 2009: 206-207, Tatsumi 2010: 26-27, Pym 2011: 1, Flanagan/Christensen 2014: 257, Teixeira 2014: 16)
Summary
Today all professional translators interact with technology, and drawing on the field of Human-Computer Interaction, O’Brien (2012) characterises translation as Translator-Computer Interaction (TCI). A new machine may offer resistance in the sense that it does not perform as intended by the scientist, and the scientist may accommodate this by for example changing the material form of the machine Taking this theoretical perspective as a point of departure, similar to Olohan (2011), TCI may be seen as a “dance of agency”, in which a human agent (translator) interacts with a non-human agent (the technology) in a process of resistance and accommodation. In order to accommodate the resistances offered by the tool, translators may need to carry out certain actions enabling the ongoing interaction between the tool and the translator to progress (see Bundgaard et al 2016)
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