Machine translation quality in an audiovisual context

The volume of Audiovisual Translation (AVT) is increasing to meet the rising demand for data that needs to be accessible around the world. Machine Translation (MT) is one of the most innovative technologies to be deployed in the field of translation, but it is still too early to predict how it can support the creativity and productivity of professional translators in the future. Currently, MT is more widely used in (non-AV) text translation than in AVT. In this article, we discuss MT technology and demonstrate why its use in AVT scenarios is particularly challenging. We also present some potentially useful methods and tools for measuring MT quality that have been developed primarily for text translation. The ultimate objective is to bridge the gap between the tech-savvy AVT community, on the one hand, and researchers and developers in the field of high-quality MT, on the other.

Minority ethno-faith communities and social inclusion through collaborative research

With alarming suicide rates and a negative identity, Alevi youth felt invisible at school where no one knew about their faith. Through collaboration between the Alevi community, Highbury Grove secondary school and the University of Westminster, we produced lessons on Alevism for the RE curriculum. Alevi pupils helped to design and deliver this successful, inclusive curriculum project, generating considerable interest from peers and the wider school community. Consequently they report a greater sense of belonging and pride in their identity.

Defining ‘Community’ for Community Translation

Unlike community interpreting, community translation engages with the members of the community both at individual and group levels. This duality of the process makes the identification of the community as a socio-cultural entity and of its individual members all the more important. There have been several attempts to define the concept of ‘community’ in different professional and academic contexts. Mindful of the difficulty of defining community, the paper proposes three methods that can help community translators in visualizing the characteristics of the intended audience and in making informed translation decisions. The three methods, derived from user-centred translation, are scrutinized using a case study based on a real-life National Health Service (NHS) text.