In this paper, we describe a data enhancement method for developing Emily, an emotion-affective open-domain chatbot. The proposed method is based on explicitly modeling positively transitioned (PT) sentiment data from multi-turn dialogues. We construct a dialogue corpus with PT sentiment data and will release it for public use. By fine-tuning a pretrained dialogue model using the produced PT-enhanced dialogues, we are able to develop an emotion-affective open-domain chatbot exhibiting close-to-human performance in various emotion-affective metrics. We evaluate Emily against a few state-of-the-art (SOTA) open-domain chatbots and show the effectiveness of the proposed approach. The corpus is made publicly available.
翻译:在本文中,我们描述了开发Emily的数据增强方法,Emily是一种情感-情感-情感-开放域域聊天机。拟议方法基于从多方向对话中明确建立积极转换(PT)感知数据的模型。我们用PT感知数据构建一个对话程序,供公众使用。通过使用制作的PT-增强型对话对预先培训的对话模式进行微调,我们可以开发出一种情感-情感-情感-情感-开放域聊天机,展示各种情感-情感-情感性能指标中的亲近人性表现。我们评估Emily相对于少数最先进的(SOTA)开放域聊天机(SOTA),并展示拟议方法的有效性。该程序被公布于众。