In communication, a human would recognize the emotion of an interlocutor and respond with an appropriate emotion, such as empathy and comfort. Toward developing a dialogue system with such a human-like ability, we propose a method to build a dialogue corpus annotated with two kinds of emotions. We collect dialogues from Twitter and annotate each utterance with the emotion that a speaker put into the utterance (expressed emotion) and the emotion that a listener felt after listening to the utterance (experienced emotion). We built a dialogue corpus in Japanese using this method, and its statistical analysis revealed the differences between expressed and experienced emotions. We conducted experiments on recognition of the two kinds of emotions. The experimental results indicated the difficulty in recognizing experienced emotions and the effectiveness of multi-task learning of the two kinds of emotions. We hope that the constructed corpus will facilitate the study on emotion recognition in a dialogue and emotion-aware dialogue response generation.
翻译:在交流中,人类会认识到对话者的情感,并以适当的情感(如同情和舒适)回应。为了发展具有这种人性的能力的对话系统,我们提议了一种方法来建立一个带有两种情感的对话程序。我们从Twitter收集对话,对每个演讲者在发声(表达情感)和听众在听发声(体验情感)后感受到的情感进行说明。我们用这种方法在日本建立了一个对话程序,其统计分析揭示了表达的情感和经历的情感之间的差异。我们进行了两种情感认识的实验。实验结果表明,难以认识经历的情感,难以认识两种情感的多任务学习的效果。我们希望构建的这个程序将有助于在对话和情感对话中进行情感认知的研究,也难以了解情绪对话反应的产生。