Call tagging using machine learning model

Abstract

Systems and methods disclosed relate to contextually tagging statements associated with calls. In particular, the contextual tagging is directed to training a call tagging model for predicting one or more categories associated with a statement for tagging. The disclosed technology generates training data for training the call tagging model based on a list of known phrases used in contacts in a contextual category and matching phrases and words in the list of known phrases against words and phrases used in statements in sample call transcripts. The call tagging model is fine-tuned by using sample statements that appear in contacts. Once trained, the call tagging model is used to determine a probability distribution of categories associated with statements in a contact and further determine contact-level category distributions using multi-dimensional vectors. The tagged contacts are used to determine contacts that are contextually similar to a given contact.