Abstract

In recent years, especially since the pandemic, video conferencing tools have been used significantly more compared to the past and have reached a wide spectrum in terms of the areas used, especially in education and research. However, when it comes to conducting online experiments, these tools do not provide enough customization for the researcher and there was a need for a platform to conduct customizable remote experiments. Experimental Hub is an open-source platform that helps researchers design and conduct customizable online experiments. In Experimental Hub, intervention by an experimenter is only possible via voice channels. Our goal is to add intervention possibilities using text, improve communication between researchers and participants, also enable a setup where communication modalities can be transformed to each other. In this work, we introduced a chat feature and the concept of "Chat filters". These filters serve as dynamic functions applied during textual communication, facilitating the analysis and manipulation of sentences. Chat user interface now allows messaging and message viewing, while the chat infrastructure processes incoming data in the background. This unlocks opportunities for multi-modal communication, leveraging the power of generative artificial intelligence and Large Language Models.

Results/Implementation/Project Description

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