%0 Journal Article
%T Automatic Satisfaction Analysis in Call Centers Considering Global Features of Emotion and Duration<br>Automatic Satisfaction Analysis in Call Centers Considering Global Features of Emotion and Duration
%A Jing Liu
%A Chaomin Wang
%A Yingnan Zhang
%A Pengyu Cong
%A Liqiang Xu
%A Zhijie Ren
%A Jin Hu
%A Xiang Xie
%A Junlan Feng
%A Jingming Kuang
%J 北京理工大学学报（自然科学中文版)
%D 2018
%R 10.15918/j.jbit1004-0579.201827.0108
%X Analysis of customers' satisfaction provides a guarantee to improve the service quality in call centers. In this paper, a novel satisfaction recognition framework is introduced to analyze the customers' satisfaction. In natural conversations, the interaction between a customer and its agent take place more than once. One of the difficulties insatisfaction analysis at call centers is that not all conversation turns exhibit customer satisfaction or dissatisfaction. To solve this problem, an intelligent system is proposed that utilizes acoustic features to recognize customers' emotion and utilizes the global features of emotion and duration to analyze the satisfaction. Experiments on real-call data show that the proposed system offers a significantly higher accuracy in analyzing the satisfaction than the baseline system. The average F value is improved to 0.701 from 0.664.<br>Analysis of customers' satisfaction provides a guarantee to improve the service quality in call centers. In this paper, a novel satisfaction recognition framework is introduced to analyze the customers' satisfaction. In natural conversations, the interaction between a customer and its agent take place more than once. One of the difficulties insatisfaction analysis at call centers is that not all conversation turns exhibit customer satisfaction or dissatisfaction. To solve this problem, an intelligent system is proposed that utilizes acoustic features to recognize customers' emotion and utilizes the global features of emotion and duration to analyze the satisfaction. Experiments on real-call data show that the proposed system offers a significantly higher accuracy in analyzing the satisfaction than the baseline system. The average F value is improved to 0.701 from 0.664.
%K satisfaction analysis emotion recognition call centers global features of emotion and duration&lt
%K br&gt
%K satisfaction analysis emotion recognition call centers global features of emotion and duration
%U http://journal.bit.edu.cn/yw/bjlgyw/ch/reader/view_abstract.aspx?file_no=20180107&flag=1