This paper presents the slurk software, a lightweight interaction server for setting up dialog data collections and running experiments. Slurk enables a multitude of settings including text-based, speech and video interaction between two or more humans or humans and bots, and a multimodal display area for presenting shared or private interactive context. The software is implemented in Python with an HTML and JS frontend that can easily be adapted to individual needs. It also provides a setup for pairing participants on common crowdworking platforms such as Amazon Mechanical Turk and some example bot scripts for common interaction scenarios.
@article{arxiv.2202.01155,
title = {The slurk Interaction Server Framework: Better Data for Better Dialog Models},
author = {Jana Götze and Maike Paetzel-Prüsmann and Wencke Liermann and Tim Diekmann and David Schlangen},
journal= {arXiv preprint arXiv:2202.01155},
year = {2022}
}