Human language expression is based on the subjective construal of the situation instead of the objective truth conditions, which means that speakers' personalities and emotions after cognitive processing have an important influence on conversation. However, most existing datasets for conversational AI ignore human personalities and emotions, or only consider part of them. It's difficult for dialogue systems to understand speakers' personalities and emotions although large-scale pre-training language models have been widely used. In order to consider both personalities and emotions in the process of conversation generation, we propose CPED, a large-scale Chinese personalized and emotional dialogue dataset, which consists of multi-source knowledge related to empathy and personal characteristic. These knowledge covers gender, Big Five personality traits, 13 emotions, 19 dialogue acts and 10 scenes. CPED contains more than 12K dialogues of 392 speakers from 40 TV shows. We release the textual dataset with audio features and video features according to the copyright claims, privacy issues, terms of service of video platforms. We provide detailed description of the CPED construction process and introduce three tasks for conversational AI, including personality recognition, emotion recognition in conversations as well as personalized and emotional conversation generation. Finally, we provide baseline systems for these tasks and consider the function of speakers' personalities and emotions on conversation. Our motivation is to propose a dataset to be widely adopted by the NLP community as a new open benchmark for conversational AI research. The full dataset is available at https://github.com/scutcyr/CPED.
翻译:人类语言的表达是基于对形势的主观曲解,而不是客观的真相条件,这意味着在认知处理后,发言者的个性和情感对对话有重要影响;然而,大多数现有对话AI的数据集忽视了人的个性和情绪,或仅考虑其中的一部分;对话系统很难理解发言者的个性和情绪,尽管大规模使用大规模培训前语言模式;为了在对话生成过程中既考虑个性和情感,我们提议采用中国人性化和情感性化对话数据集,即大规模中国人性化对话个人化和情感对话数据集,其中包括与同感和个人特征有关的多源知识。这些知识涵盖性别、五大个个个个个个个个性特征、13个情感、19个对话动作和10个场景。在40个电视节目中,有超过392个发言者的对话。我们根据版权主张、隐私问题、视频平台服务条件,发布带有音频特点的文本数据集。我们详细描述中国人性化和情感对话/情感对话的新进程,并介绍对话的三项任务,包括个性识别、情感识别以及作为个性化和情感感官和情感感官感官感官感官的访谈。最后,我们将在线对话的系统作为在线数据定位的基线和感官分析。