TY - GEN

T1 - Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys

AU - Cao, Yong

AU - Chen, Min

AU - Hershcovich, Daniel

PY - 2024

Y1 - 2024

N2 - The cultural landscape of interactions with dialogue agents is a compelling yet relatively unexplored territory. It’s clear that various sociocultural aspects—from communication styles and beliefs to shared metaphors and knowledge—profoundly impact these interactions. To delve deeper into this dynamic, we introduce cuDialog, a first-of-its-kind benchmark for dialogue generation with a cultural lens. We also develop baseline models capable of extracting cultural attributes from dialogue exchanges, with the goal of enhancing the predictive accuracy and quality of dialogue agents. To effectively co-learn cultural understanding and multi-turn dialogue predictions, we propose to incorporate cultural dimensions with dialogue encoding features. Our experimental findings highlight that incorporating cultural value surveys boosts alignment with references and cultural markers, demonstrating its considerable influence on personalization and dialogue quality. To facilitate further exploration in this exciting domain, we publish our benchmark publicly accessible at https://github.com/yongcaoplus/cuDialog.

AB - The cultural landscape of interactions with dialogue agents is a compelling yet relatively unexplored territory. It’s clear that various sociocultural aspects—from communication styles and beliefs to shared metaphors and knowledge—profoundly impact these interactions. To delve deeper into this dynamic, we introduce cuDialog, a first-of-its-kind benchmark for dialogue generation with a cultural lens. We also develop baseline models capable of extracting cultural attributes from dialogue exchanges, with the goal of enhancing the predictive accuracy and quality of dialogue agents. To effectively co-learn cultural understanding and multi-turn dialogue predictions, we propose to incorporate cultural dimensions with dialogue encoding features. Our experimental findings highlight that incorporating cultural value surveys boosts alignment with references and cultural markers, demonstrating its considerable influence on personalization and dialogue quality. To facilitate further exploration in this exciting domain, we publish our benchmark publicly accessible at https://github.com/yongcaoplus/cuDialog.

M3 - Article in proceedings

SP - 929

EP - 945

BT - Findings of the Association for Computational Linguistics: EACL 2024

PB - Association for Computational Linguistics (ACL)

T2 - 18th Conference of the European Chapter of the<br/>Association for Computational Linguistics - EACL 2024

Y2 - 17 March 2024 through 22 March 2024

ER -