Abstract
The construction of spoken dialog systems today relies heavily on appropriate corpora, but corpus selection is more an art than a science. As interaction style properties govern many aspects of dialog, they have the potential to be useful for relating and comparing corpora. This paper overviews a recently-developed model of interaction styles and shows how it can be used to identify relevant corpus differences, estimate corpus similarity, and flag likely outlier dialogs.- Anthology ID:
- 2022.sigdial-1.23
- Volume:
- Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue
- Month:
- September
- Year:
- 2022
- Address:
- Edinburgh, UK
- Editors:
- Oliver Lemon, Dilek Hakkani-Tur, Junyi Jessy Li, Arash Ashrafzadeh, Daniel Hernández Garcia, Malihe Alikhani, David Vandyke, Ondřej Dušek
- Venue:
- SIGDIAL
- SIG:
- SIGDIAL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 225–230
- Language:
- URL:
- https://aclanthology.org/2022.sigdial-1.23
- DOI:
- 10.18653/v1/2022.sigdial-1.23
- Cite (ACL):
- Nigel Ward. 2022. Using Interaction Style Dimensions to Characterize Spoken Dialog Corpora. In Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 225–230, Edinburgh, UK. Association for Computational Linguistics.
- Cite (Informal):
- Using Interaction Style Dimensions to Characterize Spoken Dialog Corpora (Ward, SIGDIAL 2022)
- PDF:
- https://preview.aclanthology.org/corrections-2024-05/2022.sigdial-1.23.pdf