论文标题
迈向情感感会话代理人
Towards a Sentiment-Aware Conversational Agent
论文作者
论文摘要
在本文中，我们根据两个模型提出了一个端到端情感感知的对话代理：答复情绪预测模型，该模型利用对话的上下文来预测适当的情绪，以便代理在其答复中表达出来；以及一个基于预测的情感和对话的上下文来制作的文本生成模型，以产生既适合上下文又适合情感的答复。此外，我们建议使用情感分类模型来评估代理商在模型开发过程中所表达的情感。这使我们能够自动评估代理。自动和人类评估结果都表明，用预定义的一组句子明确指导文本生成模型导致了明确的改进，包括表达的情感和生成文本的质量。
In this paper, we propose an end-to-end sentiment-aware conversational agent based on two models: a reply sentiment prediction model, which leverages the context of the dialogue to predict an appropriate sentiment for the agent to express in its reply; and a text generation model, which is conditioned on the predicted sentiment and the context of the dialogue, to produce a reply that is both context and sentiment appropriate. Additionally, we propose to use a sentiment classification model to evaluate the sentiment expressed by the agent during the development of the model. This allows us to evaluate the agent in an automatic way. Both automatic and human evaluation results show that explicitly guiding the text generation model with a pre-defined set of sentences leads to clear improvements, both regarding the expressed sentiment and the quality of the generated text.
