Measuring quality in translation for dubbing: a quality assessment model proposal for trainers and stakeholders

Abstract

Quality assessment in the field of Audiovisual Translation (AVT) has been addressed by several scholars, particularly in relation to interlingual subtitling (Pedersen, 2017; Robert & Remael, 2016), intralingual live subtitling (Romero-Fresco & Martínez Pérez, 2015) and interlingual live subtitling (Robert & Remael, 2017; Romero-Fresco & Pöchhacker, 2017), but to-date no model in relation to dubbing has been proposed. As with other AVT modes, the need for a quality assessment method in dubbing arises in academic and in-house training contexts. Moreover, localization companies often resort to ‘entry tests’ before engaging translators. Self-assessment also proves to be one of the main challenges for trainees in a dubbing training context, and any quality assessment tools can possibly be of help. This paper proposes a tentative quality assessment model that attempts to pin down the ‘errors’ in a dubbing dialogue script while measuring the quality via a percentage score system. The model focuses on the translation and adaptation phase in the dubbing workflow and is therefore based on a set of textual quality parameters. These are drawn on a revisited taxonomy of dubbing quality standards (Spiteri Miggiani, 2021a, 2021b), further adapted from Chaume (2007), which takes into account the dubbed end product as a whole. The model combines an end product-oriented approach with workflow-oriented standards and expectation norms, therefore taking the industry perspective into account. This implies considering the functionality of a dubbing script as a macro quality parameter in its own right. The application of this tentative model has so far been limited to the author’s academic and in-house training settings. This paper, therefore, is simply intended as a point of departure to pave the way towards applied and collaborative research that could test, validate, and further develop the proposed model.