论文标题
什么时候笑，有多难？一种检测幽默及其强度的多模式方法
When to Laugh and How Hard? A Multimodal Approach to Detecting Humor and its Intensity
论文作者
论文摘要
喜剧电视节目中伴随着对话的笑声伴随着笑声，鼓励观众清楚地标志着节目中的幽默时刻。我们提出了一种使用多模式数据在朋友电视节目中自动检测幽默的方法。我们的模型能够认识到话语是否幽默并评估其强度。我们在节目中使用预先记录的笑声作为注释，因为它标志着幽默，听众的笑声的长度告诉我们一个给定的笑话有多有趣。我们在训练阶段没有接触模型的情节上评估模型。我们的结果表明，该模型能够正确地检测出幽默的时间是幽默的78％，并且观众的笑声反应应持续多长时间，而绝对的绝对误差为600毫秒。
Prerecorded laughter accompanying dialog in comedy TV shows encourages the audience to laugh by clearly marking humorous moments in the show. We present an approach for automatically detecting humor in the Friends TV show using multimodal data. Our model is capable of recognizing whether an utterance is humorous or not and assess the intensity of it. We use the prerecorded laughter in the show as annotation as it marks humor and the length of the audience's laughter tells us how funny a given joke is. We evaluate the model on episodes the model has not been exposed to during the training phase. Our results show that the model is capable of correctly detecting whether an utterance is humorous 78% of the time and how long the audience's laughter reaction should last with a mean absolute error of 600 milliseconds.
