Connected yet Distant: An Experimental Study into the Visual Needs of the Interpreter in Remote Simultaneous Interpreting

Remote simultaneous interpreting (RSI) draws on Information and Communication Technologies to facilitate multilingual communication by connecting conference interpreters to in-presence, virtual or hybrid events. Early solutions for RSI involved interpreters working in interpreting booths with ISOstandardised equipment. However, in recent years, cloud-based solutions for RSI have emerged, with innovative Simultaneous Interpreting Delivery Platforms (SIDPs) at their core, enabling RSI delivery from anywhere. SIDPs recreate the interpreter's console and work environment (Braun 2019) as a bespoke software/videoconferencing platform with interpretation-focused features. Although initial evaluations of SIDPs were conducted before the Covid-19 pandemic (e.g., DG SCIC 2019), research on RSI (booth-based and software-based) remains limited. Pre-pandemic research shows that RSI is demanding in terms of information processing and mental modelling (Braun 2007; Moser-Mercer 2005), and suggests that the limited visual input available in RSI constitutes a particular problem (Mouzourakis 2006; Seeber et al. 2019). Besides, initial explorations of the cloud-based solutions suggest that there is room for improving the interfaces of widely used SIDPs (Bujan and Collard 2021; DG SCIC 2019). The experimental project presented in this paper investigates two aspects of SIDPs: the design of the interpreter interface and the integration of supporting technologies. Drawing on concepts and methods from user experience research and human-computer interaction, we explore what visual information is best suited to support the interpreting process and the interpreter-machine interaction, how this information is best presented in the interface, and how automatic speech recognition can be integrated into an RSI platform to aid/augment the interpreter's source-text comprehension.