Instruction Clarification Requests in Multimodal Collaborative Dialogue Games: Tasks, and an Analysis of the CoDraw Dataset

Madureira, Brielen and Schlangen, David

In visual instruction-following dialogue games, players can engage in repair mechanisms in face of an ambiguous or underspecified instruction that cannot be fully mapped to actions in the world. In this work, we annotate Instruction Clarification Requests (iCRs) in CoDraw, an existing dataset of interactions in a multimodal collaborative dialogue game. We show that it contains lexically and semantically diverse iCRs being produced self-motivatedly by players deciding to clarify in order to solve the task successfully. With 8.8k iCRs found in 9.9k dialogues, CoDraw-iCR (v1) is a large spontaneous iCR corpus, making it a valuable resource for data-driven research on clarification in dialogue. We then formalise and provide baseline models for two tasks: Determining when to make an iCR and how to recognise them, in order to investigate to what extent these tasks are learnable from data.

In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , 2023
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@inproceedings{Madureira-2023,
  title = {Instruction Clarification Requests in Multimodal Collaborative Dialogue Games: Tasks, and an Analysis of the {C}o{D}raw Dataset},
  author = {Madureira, Brielen and Schlangen, David},
  editor = {Vlachos, Andreas and Augenstein, Isabelle},
  booktitle = {Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics},
  month = may,
  year = {2023},
  address = {Dubrovnik, Croatia},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/2023.eacl-main.169},
  doi = {10.18653/v1/2023.eacl-main.169},
  pages = {2303--2319}
}