We present a human evaluation of the usefulness of conceptual route graphs (CRGs) when it comes to route following using spoken route descriptions. We describe a method for data-driven semantic interpretation of route de-scriptions into CRGs. The comparable performances of human participants in sketching a route using the manually transcribed CRGs and the CRGs produced on speech recognized route descriptions indicate the robustness of our method in preserving the vital conceptual information required for route following despite speech recognition errors.