دانلود مقاله رشته مترجمی زبان انگلیسی با موضوع مدل ارزیابی کیفی داینامیک برای ترجمه Towards a Dynamic Quality Evaluation Model for Translation که شامل 23 صفحه میباشد.

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ABSTRACT
One of the dominant current methods for translation quality evaluation within the translation industry, i.e. the error typology, is seen as being static and unable to respond to new text types or varying communicative situations and this is leading to rising levels of dissatisfaction. This paper reports on findings from a benchmarking exercise carried out in collaboration with the Translation Automation User Society (TAUS) and eight of its member companies. Eleven translation quality evaluation models were benchmarked. A number of the companies profiled their translatable content according to the parameters of utility, time and sentiment. A review of quality evaluation models in domains related to professional translation leads to a list of alternative quality evaluation methods. The communication channel, the content profile and the parameters of utility, time and sentiment are merged to form building blocks towards a more dynamic quality evaluation model for translation. Examples are given for how such a model could be implemented.
KEYWORDS
Quality evaluation, quality model, professional translation.

 Introduction
The assessment of translation quality has received much attention in the academic sphere (e.g. House 1997; Nord 1997; Lauscher 2000; Brunette 2000; Colina 2003). The focus here is not on the theory of translation quality assessment, nor on its implementation in translator training, but rather on the practice of translation quality evaluation in the professional sphere where translation quality is also ever topical and contentious. Quality is closely linked with customer opinion and yet quality evaluation (QE) in the translation industry is managed by gatekeepers in the supply and demand chain who work with static evaluation models, the majority of which are based on counting errors in random samples, applying penalties and maintaining thresholds with little, if any, input from customers. What‟s more, current QE models are predicated on a static and serial model of translation production, which is not suited to the emerging models of ubiquitous computing and „everyware‟ (Cronin 2010).
Recently, TAUS, the Translation Automation User Society, registered an appetite among its members for a change in the static and normative, time-consuming modes of translation quality evaluation. It seemed that members were dissatisfied with the current „one size fits all‟ approach and with the fact that little consideration was given to variables such as content type, communicative function, end user requirements, context, perishability, or mode of translation creation (i.e. whether the translation is created by a qualified human translator, unqualified volunteer, Machine Translation (MT) or Translation Memory (TM) system or a combination of these).
Kelly and DePalma (2009) have confirmed that translation QE is problematic in an even wider context. In consultation with 30 large-scale buyers of translation services, they conclude that numerous challenges exist for quality evaluation, including subjectivity, time, inappropriate use of linguistic resources, learning curve and technology. There is, therefore, some evidence for dissatisfaction with current QE methods.