| dc.description.abstract | Telemarketing has always been an important role for the companies to communicate with customers or searching for the new opportunities. Through Telemarketing, companies can ignore the inconvenience causes by geographical barrier. And according to TPB and ECT model, Attitude and Satisfaction are two of the important factors that influence customers’ behavior. Moreover, Customers behavior can affect their purchasing behavior and repurchasing behavior as well. That being said, Attitude and Satisfaction are one of the most important factors that determine company’s growth rate.
In past research, Attitude and Satisfaction are receiving through questionnaire or focus group. These two methods can’t really give the company real-time data, while in Telemarketing, real -time analyze is an important issue. Furthermore, among the research with Sound, most of them are related to sentiment and emotion. There’s no related work show the connection between sound and attitude or satisfaction. Therefore, this research is using speech analysis to determine customer’s attitude and satisfaction.
We collected data through our own experiment, extract speech feature to label it. Then using RNN and LSTM to train the models to identify customer’s attitude and satisfaction. In the result, we are able to identify attitude and satisfaction through speech with 70% of accuracy. This result is better than traditional SVM classification. Companies can thus apply this method into Telemarketing, to create real-time attitude and satisfaction information while communication. This can provide the company with better strategy within marketing and create a bigger opportunity for the company.
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