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Anger detection in call center dialogues
2015
2015 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)
We present a method to classify fixed-duration windows of speech as expressing anger or not, which does not require speech recognition, utterance segmentation, or separating the utterances of different speakers and can, thus, be easily applied to real-world recordings. We also introduce the task of ranking a set of spoken dialogues by decreasing percentage of anger duration, as a step towards helping call center supervisors and analysts identify conversations requiring further action. Our work
doi:10.1109/coginfocom.2015.7390579
fatcat:g675t3tusfcojagzj5ton5vlkm