This paper presents the key findings of the pilot phase of SMART (Shaping Multilingual Access through Respeaking Technology), a multidisciplinary international project focusing on interlingual respeaking (IRSP) for real-time speech-to-text. SMART addresses key questions around IRSP feasibility, quality and competences. The pilot project is based on experiments involving 25 postgraduate students who performed two IRSP tasks (English–Italian) after a crash course. The analysis triangulates subtitle accuracy rates with participants’ subjective ratings and retrospective self-analysis. The best performers were those with a composite skillset, including interpreting/subtitling and interpreting/subtitling/respeaking. Participants indicated multitasking, time-lag, and monitoring of the speech recognition software output as the main difficulties; together with the great variability in performance, personal traits emerged as likely to affect performance. This pilot lays the conceptual and methodological foundations for a larger project involving professionals, to address a set of urgent questions for the industry.