Machine Translation and Translation Memory Systems: An Ethnographic Study of Translators’ Satisfaction

Abstract

The translator’s workplace (TW) has undergone radical changes since microcomputers were introduced on the market and, as a result, digitization increased enormously. Existing translation-related technologies, such as machine translation (MT), were enhanced and others, such as translation memory (TM) systems, were developed. It is a noteworthy fact that implementing new translation-related technologies in the TW is done in various conditions according to specific goals that subsequently define new work conditions for translators. These new work conditions affect translators’ satisfaction with their job, and their satisfaction will influence career development and employee retention in the translation industry over the long term. In the past two decades, Language Service Providers (LSPs) have started integrating MT into TM systems to benefit from MT suggestions when TM is not helpful. Neither TM nor MT is unfamiliar to the translation industry, but the combination, i.e. TM+MT, is fairly new. So far, there have been few studies on translators’ satisfaction with TM+MT. This study consists of an ethnographic research project on seven translators in a Canada-based company where TM+MT is used. Observations, semi-structured interviews, and in-house document analysis have been used as data collection methods. The data obtained has been analyzed and discussed based on Rodríguez-Castro’s task satisfaction model (2011). This model addresses intrinsic and extrinsic sources of translators’ satisfaction with the activities they do in their job. Investigating the factors and variables of her model in the aforementioned company, I concluded that those sources of satisfaction cannot be considered separately from the job-context factors, such as the company’s policies in implementing TM+MT.