System and method for automated processing of digitized speech using machine learning

A computing system for processing speech, the system comprising:

• at least one electronic processor;
• and
• a non-transitory computer readable medium storing instructions that, when executed by the at least one electronic processor, cause the electronic processor to perform operations comprising:
• obtaining a trained machine learning model, wherein the machine learning model has been trained using a cumulative historical data structure corresponding to at least one digitally-encoded speech representation for a plurality of telecommunications interactions conducted by a plurality of agent-side participants, wherein the cumulative historical data structure includes a first data corresponding to a score variable and a second data corresponding to a plurality of driver variables,
• applying the trained machine learning model to a subset of data in the cumulative historical data structure that corresponds to a first agent-side participant of the plurality of agent-side participants, to generate at least one of a performance classification score or a performance direction classification score,
• applying the trained machine learning model to identify an intervention-target agent-side participant from among the plurality of agent-side participants,
• applying the trained machine learning model to the cumulative historical data structure to identify an intervention training plan, and
• facilitating at least one training session for the intervention-target agent-side participant according to the intervention training plan.