System and method of call classification with context modeling based on composite words

Abstract

A system and method of automatically classifying a communication involving at least one human, e.g., a human-to-human telephone conversation, into predefined categories of interest, e.g., 'angry customer, etc. The system automatically, or semi-automatically with user interaction, expanding user input into semantically equivalent events. The system recognizes these events, each of which is given a confidence level, and classifies the telephone conversation based on an overall confidence level. In some embodiments, a different base unit is utilized. Instead of recognizing individual words, the system recognizes composite words, each of which is pre-programmed as an atomic unit, in a given context. The recognition includes semantically relevant composite words and contexts automatically generated by the system. The composite words based contextual recognition technique enables the system to efficiently and logically classifying and indexing large volumes of communications and audio collections such as call center calls, Webinars, live news feeds, etc.