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Emotion recognition from helpdesk messages

机译:服务台消息中的情绪识别

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摘要

This paper describes system for emotion recognition which can be used to determine the priority of messages on the first level of helpdesk services. An algorithm used in this paper uses artificial intelligence (SVM classifier) and can recognize 5 different emotions. The used emotional classes were based on acoustic model which was inspired by acoustic emotion recognition research works. The proposed system has evaluated 5 classifiers and identifies a dominant emotion class. This work also describes a small database which was created on the basis of the selected helpdesk messages. The database was used in training and testing of the mentioned classifier. Success of classifier achieved in this work is 76.63% and impact of the proposed optimization methods on the final model accuracy has been proven.
机译:本文介绍了一种情绪识别系统,该系统可用于确定服务台服务第一层上的消息优先级。本文使用的算法使用人工智能(SVM分类器),可以识别5种不同的情绪。所使用的情感类别基于声学模型,该模型受声学情感识别研究工作的启发。拟议的系统评估了5个分类器,并确定了主导情绪类别。这项工作还描述了一个小型数据库,该数据库是根据选定的帮助台消息创建的。该数据库用于训练和测试所提到的分类器。在这项工作中实现的分类器成功率为76.63%,并且已经证明了所提出的优化方法对最终模型准确性的影响。

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