We describe the components of the system for automated scoring, comprising an automatic speech recognition (ASR) system, a set of filtering models to flag nonscorable responses, linguistic measures relating to the various construct subdimensions, and multiple linear regression scoring models for each item type. Our system is set up to simulate a hybrid system whereby responses flagged as potentially nonscorable by any component of the filtering model are routed to a human rater, and all other responses are scored automatically by our system.