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A multimodal interpreter for 3D visualization and animation of verbal concepts

We present an algorithm intended to visually represent the sense of verb related to an object described in a text sequence, as a movement in 3D space. We describe a specific semantic analyzer, based on a standard verbal ontology, dedicated to the interpretation of action verbs as spatial actions. Using this analyzer, our system build a generic 3D graphical path for verbal concepts allowing space representation, listed as SelfMotion concepts in the FrameNet ontology project. The object movement is build by first extracting the words and enriching them with the semantic analyzer. Then, weight tables, necessary to obtain characteristics values (orientation, shape, trajectory...) for the verb are used in order to get a 3D path, as realist as possible. The weight tables were created to make parallel between features defined for SelfMotion verbal concept (some provided by FrameNet, other determined during the project) and values used in the final algorithm used to create 3D moving representations from input text. We evaluate our analyzer on a corpus of short sentences and presents our results.