Abstract

Quality monitoring of calls is a critical activity in call centers. Currently, it is done manually, wherein a person listens to all the recorded audio files or a random sample of audio files to check how the call center representative has performed. Quality monitoring also helps in recording the customer’s feedback, which is useful for other business activities like marketing, sales, service, etc. However, this process involves enormous amount of human effort and time besides being error prone. This paper evaluates the application of Machine Learning and Natural Language Processing algorithms in the process of assessing the call center agents.