Persona and Knowledge dual context open-domain chat is a novel dialogue generation task introduced recently. While Persona and Knowledge is each interesting context of open-domain dialogue, the combination of both has not been well studied. We tackle Persona-Knowledge identification and response generation tasks in this paper. We design an informed data augmentation strategy that is compatible with neural Q&A retrieval models. With the augmented data, we perform permutative Persona-Knowledge evaluation and successive Persona search fine-tuning. Furthermore, we perform dialogue generation with various decoding techniques and illustrate crucial elements. We achieve SOTA across official metrics with 93.99% Grounding accuracy average and 23.62 SacreBLEU score.
翻译:人与知识的双重背景开放域聊天是最近引入的新颖的对话生成任务。虽然人与知识是开放域对话的每个有趣背景,但两者的结合并没有很好地研究。我们在本文中处理人与知识的识别和反应生成任务。我们设计了一个与神经 ⁇ ⁇ A 检索模式兼容的知情数据增强战略。在增加数据后,我们进行人与知识的交互评价和相继的搜索微调。此外,我们还与各种解码技术进行对话,并展示关键要素。我们实现了SOTA, 以93.99%的测深精度平均分和23.62的SACACEBLU分数跨官方指标。