Using cloud services and machine learning to improve customer support : Study the applicability of the method on voice data

This project investigated how machine learning could be used to classify voice calls in a customer support setting. A set of a few hundred labeled voice calls were recorded and used as data. The calls were transcribed to text using a speech-to-text cloud service. This text was then normalized and used to train models able to predict new voice calls. Different algorithms were used to build the models, including support vector machines and neural networks. The optimal model, found by extensive parameter search, was found to be a support vector machine. Using this optimal model a program that can classify live voice calls was made