Empathetic Dialogue Generation with Pre-trained RoBERTa-GPT2 and External Knowledge

Ye Liu; Wolfgang Maier; Wolfgang Minker; Stefan Ultes

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arXiv · 2109.03004

Empathetic Dialogue Generation with Pre-trained RoBERTa-GPT2 and External Knowledge

Ye Liu·Wolfgang Maier·Wolfgang Minker·Stefan Ultes

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Abstract

One challenge for dialogue agents is to recognize feelings of the conversation partner and respond accordingly. In this work, RoBERTa-GPT2 is proposed for empathetic dialogue generation, where the pre-trained auto-encoding RoBERTa is utilised as encoder and the pre-trained auto-regressive GPT-2 as decoder. With the combination of the pre-trained RoBERTa and GPT-2, our model realizes a new state-of-the-art emotion accuracy. To enable the empathetic ability of RoBERTa-GPT2 model, we propose a commonsense knowledge and emotional concepts extractor, in which the commonsensible and emotional concepts of dialogue context are extracted for the GPT-2 decoder. The experiment results demonstrate that the empathetic dialogue generation benefits from both pre-trained encoder-decoder architecture and external knowledge.

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Ye Liu, Wolfgang Maier, Wolfgang Minker, Stefan Ultes. 2021-09-07. Empathetic Dialogue Generation with Pre-trained RoBERTa-GPT2 and External Knowledge. https://arxiv.org/abs/2109.03004

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