A Development of Personality Recognition Model from Conversation Voice in Call Center Context

Abstract

A call center is an important communication channel between a business and its customers. The call center staffs are responsible for resolving customer problems and fulfilling their needs. It is undeniable that customer satisfaction can be increased if personalized services relating to their characteristics such as personality are provided. Researches are suggesting that a person's personality can be recognized from his/her conversational voice. Thus, a machine learning model that recognizes each customer's personality from one's conversational voice in a call center would enable the cell center to give that one appropriate response. This study focuses on developing a personality recognition model to predict each MPI (Maudsley Personality Inventory) personality dimension from each conversational voice. The MPI personality dimension includes E-scale (representing extraversion and introversion) and N-scale (representing neuroticism and stability). Audio files of conversational voice were collected from 92 volunteers instructed to make conversation in the simulated call center context. Logistic regression, LinearSVC, Random forest, and Artificial neural networks were used in the modeling process. The result shows that the model generated by using Artificial neural networks has the best performance on predicting the E-scale. The model has the positive predictive value (Introversion prediction) and the negative predictive value (Extraversion prediction) equal to 0.71 and 0.75, respectively. No model shows satisfying performance on neuroticism and stability prediction. This study shows a piece of evidence that extraversion and introversion in MPI, which have implications in businesses, can be effectively recognized from each person's conversational voice made through call centers. The model can be beneficial in many business applications such as call center management, personalized product offering, and personalized advertisement.