Recent approaches have attempted to personalize dialogue systems by leveraging profile information into models. However, this knowledge is scarce and difficult to obtain, which makes the extraction/generation of profile information from dialogues a fundamental asset. To surpass this limitation, we introduce the Profile Generation Task (PGTask). We contribute with a new dataset for this problem, comprising profile sentences aligned with related utterances, extracted from a corpus of dialogues. Furthermore, using state-of-the-art methods, we provide a benchmark for profile generation on this novel dataset. Our experiments disclose the challenges of profile generation, and we hope that this introduces a new research direction.
翻译:最近的方法尝试通过将个人资料信息整合到模型中来个性化对话系统。然而,这些知识很少且难以获取,这使得从对话中提取/生成个人资料信息成为一项基本资产。为了超越这个限制,我们引入了个人资料生成任务(PGTask)。我们为这个问题贡献了一个新的数据集,其中包括与相关话语对齐的个人资料句子,从一个对话语料库中提取。此外,使用最先进的方法,我们提供了这个新数据集上的个人资料生成的基准。我们的实验揭示了个人资料生成的挑战,并希望引入一个新的研究方向。