Leveraging emotion detection using emotions from yes-no answers
Leveraging emotion detection using emotions from yes-no answers
复制标题
利用是非答案中的情绪进行情绪检测
DOI：
10.21437/interspeech.2008-88
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
P. Dumouchel
中科院分区：
文献类型：
--
作者：
Narjès Boufaden;P. Dumouchel
针对呼叫中心这一特定领域，我们提出了一种从人机对话中检测负面情绪和非负面情绪的新方法。我们认为，在不使用额外的语言或上下文信息的情况下，改进情绪检测是可能的。我们发现，无答案是情感显著的词，利用无答案话轮的高准确率可以提高人机对话分类的准确性。我们还表明，使用神经网络和支持向量机作为基本模型的堆叠泛化提高了每个模型的精度，而无模型和对话模型的组合将单独的对话模型的精度提高了13%。
We present a new approach for the detection of negative versus non-negative emotions from Human-computer dialogs in the specific domain of call centers. We argue that it is possible to improve emotion detection without using additional information being linguistic or contextual. We show that no-answers are emotional salient words and that it is possible to improve the accuracy of the classification of Human-computer dialogs by taking advantage of the high accuracy achieved on no-answer turns. We also show that stacked generalization using neural networks and SVM as base models improves the accuracy of each model while the combination of the no-model and the dialog model improves the accuracy of the dialog-model alone by 13%.