论文标题
botstalk：用于自动策划大规模多技能对话数据集的机器源框架
BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets
论文作者
论文摘要
为了建立能够使用多种交流技能的开放域聊天机器人，我们提出了一个新颖的框架botstalk，其中多个以特定目标技能为基础的代理人参加了对话，以自动注释多技能对话。我们进一步介绍了混合技能僵尸史塔（BSBT），这是一个包括300K对话的大型多技能对话数据集。通过广泛的实验，我们证明了我们的数据集对需要了解技能融合以及技能接地的多技能对话系统有效。我们的代码和数据可在https://github.com/convei-lab/botstalk上找到。
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.
