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    <abstract>To build open-domain chatbots that are able to use diverse communicative skills, we propose a novel framework BotsTalk, where multiple agents grounded to the specific target skills participate in a conversation to automatically annotate multi-skill dialogues. We further present Blended Skill BotsTalk (BSBT), a large-scale multi-skill dialogue dataset comprising 300K conversations. Through extensive experiments, we demonstrate that our dataset can be effective for multi-skill dialogue systems which require an understanding of skill blending as well as skill grounding. Our code and data are available at https://github.com/convei-lab/BotsTalk.</abstract>
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%0 Conference Proceedings
%T BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets
%A Kim, Minju
%A Kim, Chaehyeong
%A Song, Yong Ho
%A Hwang, Seung-won
%A Yeo, Jinyoung
%Y Goldberg, Yoav
%Y Kozareva, Zornitsa
%Y Zhang, Yue
%S Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates
%F kim-etal-2022-botstalk
%X To build open-domain chatbots that are able to use diverse communicative skills, we propose a novel framework BotsTalk, where multiple agents grounded to the specific target skills participate in a conversation to automatically annotate multi-skill dialogues. We further present Blended Skill BotsTalk (BSBT), a large-scale multi-skill dialogue dataset comprising 300K conversations. Through extensive experiments, we demonstrate that our dataset can be effective for multi-skill dialogue systems which require an understanding of skill blending as well as skill grounding. Our code and data are available at https://github.com/convei-lab/BotsTalk.
%R 10.18653/v1/2022.emnlp-main.344
%U https://aclanthology.org/2022.emnlp-main.344
%U https://doi.org/10.18653/v1/2022.emnlp-main.344
%P 5149-5170

Markdown (Informal)

[BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets](https://aclanthology.org/2022.emnlp-main.344) (Kim et al., EMNLP 2022)

• BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets (Kim et al., EMNLP 2022)

ACL

• Minju Kim, Chaehyeong Kim, Yong Ho Song, Seung-won Hwang, and Jinyoung Yeo. 2022. BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 5149–5170, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.