  A large portion of the car-buying experience in the United States involves
interactions at a car dealership. At the dealership, the car-buyer relays their
needs to a sales representative. However, most car-buyers are only have an
abstract description of the vehicle they need. Therefore, they are only able to
describe their ideal car in "car-speak". Car-speak is abstract language that
pertains to a car's physical attributes. In this paper, we define car-speak. We
also aim to curate a reasonable data set of car-speak language. Finally, we
train several classifiers in order to classify car-speak.
