# Personalized and Emotional Conversation

1 papers with code • 1 benchmarks • 1 datasets

Personalized and Emotional Conversation (PEC) is defined as follows: Given the personalized information ($P_{R1}$ and $P_{R2}$) of two speakers, their conversation context $C$, the emotion $E_K$ and DA $D_K$ of the response to be generated, and the personalized information $P_{K}$ of the responder, the goal is to generate an anthropomorphic response $Y$. $$Y = argmax_{Y'}P(Y'|C, E_K, D_K, P_K) \label{task_definition}$$

Particularly, context $C={(U_1,E_1,D_1,P_1),\cdots,(U_{K-1},E_{K-1},D_{K-1},P_{K-1})}$ contains multi-turn conversation content (i.e., utterance $U_i$), emotion $E_i$ of the associated utterance, DA $D_i$ of the associated utterance, and personalized information $P_i$ of the associated speaker.

# CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset for Conversational AI

29 May 2022

Finally, we provide baseline systems for these tasks and consider the function of speakers' personalities and emotions on conversation.

1