A Language Visualization System

In this thesis, a novel language visualization system is presented that converts natural language text into 3D scenes. The system is capable of understanding some concrete nouns, visualizable adjectives and spatial prepositions from full natural language sentences and generating 3D static scenes using these sentences. It is a rule based system that uses natural language processing tools, 3D model galleries and language resources during the process. Several techniques are shown that deals with the generality and ambiguity of the language in order to visualize the natural language text. A question answering module is built as well to answer certain types of spatial inference questions after the scene generation process is completed. The system demonstrates a new way of solving spatial inference problems by not only using the language itself but with the extra information provided by the visualization process.