  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.
