论文标题
emptransfo：用于创建同理心对话系统的多头变压器体系结构
EmpTransfo: A Multi-head Transformer Architecture for Creating Empathetic Dialog Systems
论文作者
论文摘要
理解情绪并相应地做出反应是对话系统的最大挑战之一。本文介绍了Emptransfo，这是一种多头变压器体系结构，用于创建同理心对话系统。尽管可以使用具有不同尺寸的模型，但Emptransfo利用了最先进的预培训模型（例如OpenAI-GPT）来生成语言。我们表明，利用情绪和其他元数据的历史可以通过对话系统提高所产生的对话的质量。我们使用具有挑战性语言语料库的实验结果表明，所提出的方法以HIT@1和PPL（PLEXITY）的方式优于其他模型。
Understanding emotions and responding accordingly is one of the biggest challenges of dialog systems. This paper presents EmpTransfo, a multi-head Transformer architecture for creating an empathetic dialog system. EmpTransfo utilizes state-of-the-art pre-trained models (e.g., OpenAI-GPT) for language generation, though models with different sizes can be used. We show that utilizing the history of emotions and other metadata can improve the quality of generated conversations by the dialog system. Our experimental results using a challenging language corpus show that the proposed approach outperforms other models in terms of Hit@1 and PPL (Perplexity).
