Embracing the complexity

Embracing the complexity: hybrid practices for interlingual communication in real time

The term speech-to-text is normally associated with full automation of spoken communication (i.e. technology-driven transformation of spoken input into written output, particularly in real-time). The rapid development of technologies driven by artificial intelligence, like automatic speech recognition and machine translation, has opened up a myriad of hybrid methods and possible configurations for real-time delivery of speech-to-text. These can be positioned at the crossroads of translation, interpreting, and subtitling and entail different degrees of human and machine input to provide what is ultimately the same product: live text in a different language. However, we still do not know much about the affordances and constraints brought about by different workflows, and how they can match different live communication scenarios.

This panel discussed the current state of the art in terms of speech-to-text interlingual practices, attempting to provide a clear and comprehensive overview of what these practices are and where they can be placed on a continuum from human-centric to automated ones. This serves as a springboard to capture and systematise the complexity of the current landscape, in a way that emphasises the hybrid nature of these practices and the role that language professionals play in different processes.

The panel brought together experts from a variety of backgrounds, attempting to converge on a topical and multifaceted issue that requires input from a variety of standpoints to be addressed in all its complexity. Invited panellists used their own unique perspectives (institutional, professional, academic, industry- and user-centred) to discuss how we can bring about and capitalise on the intelligent and responsible integration of human skills and technological capabilities for the benefit of all stakeholders involved.