Target Guided Emotion Aware Chat Machine

Autor:	Wei, Wei, Liu, Jiayi, Mao, Xianling, Guo, Guibin, Zhu, Feida, Zhou, Pan, Hu, Yuchong, Feng, Shanshan
Rok vydání:	2020
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge is not well addressed in the literature, since most of the approaches neglect the emotional information conveyed by a post while generating responses. This article addresses this problem by proposing a unifed end-to-end neural architecture, which is capable of simultaneously encoding the semantics and the emotions in a post and leverage target information for generating more intelligent responses with appropriately expressed emotions. Extensive experiments on real-world data demonstrate that the proposed method outperforms the state-of-the-art methods in terms of both content coherence and emotion appropriateness. Comment: To appear on TOIS 2021
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2011.07432 Zobrazit plný text záznamu View this record from Arxiv