Interactional Competence and Practice in a Second Language (ICOP-L2) Denmark

We were at the 4th international conference on Interactional Competences and Practices in the Second Language (ICOP-L2), held this year at the University of Southern Denmark in Kolding, Denmark, 5-7 June 2024.

We presented our work with Ufonia, here looking at differences between first- and second-language speakers when they engage with conversational user interfaces, and what implications there are for Conversation Design.

i-Competence and i-Practice? L2 interaction in the era of the Conversational User Interface

Voice-based Conversational User Interfaces (CUIs or VUIs) are being rapidly adopted by service providers and other organisations seeking to automate interactions with customers and clients. Indeed, it is becoming increasingly rare to speak with a human agent when contacting an organisation.

Ensuring that these ‘conversations’ are successful is challenging both for the conversation designers and engineers developing the technologies underpinning the CUI; and to anyone else required to engage with the CUI. To enable this, engineers rely on a range of technologies, such as speech recognition and Natural Language Processing and Understanding (NLP/NLU), to ensure the system understands the speech of the human client, and to generate speech that is understandable and appropriate for the type of activity.

This becomes exponentially more challenging in interactions where the client’s speech deviates from that on which the machines have been trained, including that of L2 speakers. Such clients may face situations where their speech is unrecognised or wrongly processed by the machine. In the absence of a human interlocutor who may be able to adjust to this, this could lead to false outcomes, disengagement and marginalisation.

This presentation reports on work carried out by the authors in partnership with healthcare start-up Ufonia. The company has developed a voice assistant, Dora, for carrying out routine clinical conversations across a number of hospital trusts (see Brandt et al. 2023). Using insights and methods from Conversation Analysis, the collaboration has worked to ensure that these conversation-framed user activities achieve the institutional aims of the phone-call, while providing an acceptable experience for the user. Specifically, here we report on how the recent adoption of Large Language Model (LLM) technology for carrying out these activities has opened up further opportunities to leverage Applied Linguistics to help train the CUIs in recipient design for L2 users.

You can read about this work here