Abstract
Customer complaint has been the important feedback for modern enterprises to improve their product and service quality as well as the customer's loyalty. As one of the commonly used manners in customer complaint, telephone communication carries rich emotional information of speeches, which provides valuable resources for perceiving the customer's satisfaction and studying the complaint handling skills. This paper studies the characteristics of telephone complaint speeches and proposes an analysis method based on affective computing technology, which can recognize the dynamic changes of customer emotions from the conversations between the service staff and the customer. The recognition process includes speaker recognition, emotional feature parameter extraction, and dynamic emotion recognition. Experimental results show that this method is effective and can reach high recognition rates of happy and angry states. It has been successfully applied to the operation quality and service administration in telecom and Internet service company.
Highlights
Customer service has been playing an increasing important role in the competitive market in business administration in recent years
Mel Frequency Cepstrum Coefficient (MFCC) parameters usually perform better than the other spectral parameters and are widely applied to speech recognition [18]
Back-Propagation Neural Network (BPNN) is one of the most widely used artificial neural networks, and it adopts a kind of error back-propagation algorithm for training multilayer feed forward neural network
Summary
Customer service has been playing an increasing important role in the competitive market in business administration in recent years. An Computational Intelligence and Neuroscience effective technology, which is independent of the speakers’ emotional changes [10], should be first utilized to precisely distinguish the customer’s speeches from those of the service staff ’s On this basis, the conversations in telephone complaints can be segmented into separate speeches according to their different speakers. Contempt, disgust, distress, fear, guilt, interest, joy, shame, and surprise
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
