论文标题
情感条件创意对话世代
Emotion Conditioned Creative Dialog Generation
论文作者
论文摘要
我们提出了一个基于拨号的模型，用于生成根据以下情绪之一来调节的创新对话响应：愤怒，厌恶，恐惧，幸福，痛苦，悲伤和惊喜。我们的模型能够给定输入句子和所需的情感标签产生上下文响应。我们的模型能够以0.6的精度表达所需的情绪。表现最好的情绪是中立，恐惧和厌恶。在衡量表达情感的力量时，我们发现模型以最强烈的方式表达了愤怒，恐惧和厌恶。
We present a DialGPT based model for generating creative dialog responses that are conditioned based on one of the following emotions: anger, disgust, fear, happiness, pain, sadness and surprise. Our model is capable of producing a contextually apt response given an input sentence and a desired emotion label. Our model is capable of expressing the desired emotion with an accuracy of 0.6. The best performing emotions are neutral, fear and disgust. When measuring the strength of the expressed emotion, we find that anger, fear and disgust are expressed in the most strong fashion by the model.
